Explore the top intent data platforms, key features, and strategic benefits to boost your B2B marketing and sales in 2025. Stay competitive and informed.

With so much competition today in B2B marketing, figuring out buyer behavior as it happens is crucial. Now, intent data allows marketers to locate, reach out to, and influence highly valued leads based on what they do online. In 2025, intent data platforms will have advanced to provide more detailed information, better fit into our processes, and stronger intelligence to boost lead generation efforts. If you are a marketer trying to improve how fast your pipeline fills up or a sales leader wanting to stay on top of outreach, using intent data can completely change the way you work.
In this article, we look at the top intent data platforms available in 2025, learn how to benefit from them, see their standout features, and discover how they can improve your B2B lead generation process.

Table of Contents:
1. Best Intent Data Platforms in 2025
1.1. Bombora
1.2. ZoomInfo (Intent + Scoops)
1.3. 6sense
1.4. Demandbase One
1.5. Leadfeeder (now Dealfront)
2. How to Use Intent Data for B2B Marketing
2.1. Prioritize High-Intent Accounts
2.2. Personalize Content Experiences
2.3. Enhance Account-Based Marketing (ABM)
2.4. Shorten the Sales Cycle
2.5. Improve Lead Scoring Models
2.6. Refine Paid Advertising Campaigns
2.7. Align Sales and Marketing Teams
3. Features of Top Intent Data Tools
3.1. Multi-Source Data Aggregation
3.2. Predictive Analytics & AI Modeling
3.3. Seamless CRM and MAP Integrations
3.4. Topic and Keyword-Level Tracking
3.5. Real-Time Alerts and Notifications
4. Benefits of Using Intent Data for Lead Generation
Conclusion

1. Best Intent Data Platforms in 2025

Explore the top 5 intent data platforms revolutionizing B2B marketing in 2025. Each tool is assessed for its strengths, weaknesses, standout features, and pricing.

1.1. Bombora

Bombora is chosen as the top intent data platform in 2025 for relying on numerous B2B publishers to offer detailed, third-party information. It connects right away to Salesforce, HubSpot, and LinkedIn, so activation is smooth and easy. Even though it costs $25,000 a year and is intended for large companies, it helps a lot with ABM and understanding which leads to paying attention to.

Some SMBs might object to the price and the limited customization that can be done on the platform. If your organization is large and marketing is well-established, Bombora offers the needed insights to help you lead your industry.

1.2. ZoomInfo (Intent + Scoops)

ZoomInfo is still at the forefront of the B2B data business by organizing intent, firms, tech, and detailed contact data together. You get up-to-date news through “Scoops” about major changes in a company, such as new leadership or technology investments. Intent data is linked to when a business is planning to purchase and their company profile, which supports sales teams in knowing when to act.

Even though it initially costs about $15,000 a year, and extra add-ons can be expensive, it has detailed tools for filtering and dividing data. Due to its steep learning curve, small teams may be put off, but ZoomInfo has everything needed for revenue teams seeking comprehensive, ongoing data for boosting sales across all channels.

1.3. 6sense

Using AI and predictive analytics, 6sense helps B2B marketers in 2025 notice visitors who may have gone unnoticed and prioritize those who show clear intent to buy. It reviews behavioral information gathered from digital sources to identify when someone may be ready to purchase and how to reach them using emails, advertisements, and contacting them direct.

Before implementation, a period of training and configuration is necessary, and newer teams might struggle with this part. The cost is set by the company and usually starts at $30,000 to $40,000 each year. For companies working toward a data-driven plan for every part of the pipeline, 6sense gives them an intelligent and scalable answer.

1.4. Demandbase One

Demandbase One provides top-class solutions for account-based marketing and intent data to users. Thanks to AI, it can combine information from the three main data sources to understand how potential customers behave and decide. It allows for close ad targeting, personalized website content, and fast sales updates if intent to buy increases. Made for businesses, its power is in helping tie together marketing and sales by enriching and organizing important data.

Even though it works best when linked with other martech software, Demandbase is still very useful for businesses running highly complicated ABM campaigns. Priced from around $20,000, it is suitable for companies wanting in-depth information about accounts and carefully designed engagement as buyers move through each stage.

1.5. Leadfeeder (now Dealfront)

The rebranded Dealfront gives businesses a user-friendly and meaningful way to find intent data suited for companies of all sizes. It is especially strong at turning people who visit websites anonymously into leads that can be followed up for possible sales. Therefore, any company that seeks to make the most of its website traffic without much setup will find this effective.

Leadfeeder easily connects with CRMs such as HubSpot and Pipedrive to make lead management easier. Since it doesn’t have all the AI and predictive features of 6sense, but offers a simple UI and is less expensive, it’s a good pick for smaller teams. Since the freemium option is available and the lowest monthly plan is $139, Dealfront is a cost-effective way to start working with intent data and B2B leads.

2.1. How to Use Intent Data for B2B Marketing

Discover actionable strategies to leverage intent data across the marketing funnel—from awareness to conversion.

2.2. Prioritize High-Intent Accounts

Certain account behavior is identified by intent data, allowing marketers to know when someone is looking into things like yours. By doing this, you are making sure sales and marketing teams focus on accounts that are likely to turn into sales. With the help of intent signals, tools like Bombora and 6sense focus your team members on strong leads rather than simply having them look at a lot of prospects.

2.2. Personalize Content Experiences

Using the data about what prospects look up, marketers can personalize their content distribution. When a potential buyer is researching enterprise cybersecurity, your email, ad, and landing page campaigns can be aligned with that subject. Ads and recommendations that adapt to a person’s current interests see much higher interaction.

2.3. Enhance Account-Based Marketing (ABM)

Having intent data means you know which accounts might be ready to purchase at the time of your ABM campaign. Dynamic segmentation, targeted advertising, and message changes can be made using Demandbase and 6sense based on purchasing indications. It is possible to link these insights to CRM to keep marketing and sales united.

2.4. Shorten the Sales Cycle

If you notice a prospect is doing research or thinking over a purchase, you can be proactive by giving them offers, demos, or case studies. Having intent data permits less frequent outreach to prospects, as well as better anticipation of their needs. Means like ZoomInfo combine these different signals into the regular sales work cycle.

2.5. Improve Lead Scoring Models

Generally, lead scoring in this manner is based on information about the demographics and firmographics of a person. The model performs more accurately when you include intent signals (looking at what users focus on, how often they view content, or how they compare competitors) in the scoring. With this, the platforms can automatically send nurturing messages or trigger sales alerts based on better information.

2.6. Refine Paid Advertising Campaigns

Intent data improves the way ads are aimed at key audiences on Google, LinkedIn, and programmatic platforms. You can target customers online based on their intentions or company details to show highly relevant ads. 6sense and Demandbase have native ad platforms that rely on intent data to raise click-throughs and conversions.

2.7. Align Sales and Marketing Teams

Intent data encourages openness and teamwork by letting everyone see how a prospect interacts with the company. Sales team members learn more about leads, and marketers use feedback to improve how their campaigns are run. Setting up regular ‘intent-qualified lead’ discussions can ensure every team is performing and accountable.

3. Features of Top Intent Data Tools

A closer look at the essential features that define the best intent data platforms in 2025.

3.1. Multi-Source Data Aggregation

Top platforms bring together data from people’s behavior on their websites, from other publishers, and from the companies they partner with. It gives us a complete understanding of what the buyer is looking for. Bombora and Demandbase are best at gathering insights from a company’s actions as well as its structure to achieve effective targeting.

3.2. Predictive Analytics & AI Modeling

Intent data is at its strongest when added to predictive elements. With the help of AI, 6sense and ZoomInfo can identify purchase preparation and which actions could engage accounts the most. It allows sales and marketing to use their efforts more wisely.

3.3. Seamless CRM and MAP Integrations

Good platforms often link directly with Salesforce, HubSpot, and marketing automation platforms such as Marketo or Pardot. With these integrations, data is updated instantly, workflows are started by triggers, and lead tracking and nurturing can be done from a single dashboard.

3.4. Topic and Keyword-Level Tracking

Advanced intent tools monitor particular groups of keywords so teams see which subjects are important to each account. The Bombora platform contains more than 10,000 topics related to B2B interests. It makes the campaign extremely precise and accurate.

3.5. Real-Time Alerts and Notifications

Being timely is necessary to turn your interest into a business opportunity. Demandbase and ZoomInfo report increases in activity so sales teams can react in real time. Such updates are often shared with SDRs or BDRs so they can take action right away and improve chances of closing a deal.

4. Benefits of Using Intent Data for Lead Generation

Intent data helps target people who are likely to purchase, so businesses achieve more effective and quicker lead generation. Sellers find it much easier to close deals since they focus on those who have already shown interest in buying, which streamlines the sales pipeline and leads to more profits. Marketers can also focus messages on important customer issues and the stages they pass through in the buyer journey, which increases engagement and chances of a response.
With less spending on leads not ready to buy, your marketing funds get the greatest return possible. Providing prospects with suitable messages from the outset, sales teams can often achieve results quickly and require fewer steps. It becomes simpler to qualify leads when intent signals tell you who is most willing to purchase.
Being able to match an approach to each customer’s actions helps ABM reach better performance, lays the groundwork for building real relationships, and boosts how rapidly sales increase.

Conclusion

In the coming years, reliance on intent data will grow for B2B marketers. Advanced solutions, knowledge of basic functions, and smart usage of intent trends allow businesses to draw, engage, and pursue high-intent customers more effectively. Using intent data, marketers and sales teams receive the necessary information to close deals quicker and improve their return on investment. Now is the time to fully learn it.

Visit Our SalesMarkBlog Section to Uncover the Sales Strategies That Ignite Your Sales Journey!

Discover how cookieless multi-touch attribution transforms user journey tracking with privacy-first strategies, accurate insights, and smarter marketing decisions. 

Today, digital marketers have to find new methods for tracking and measuring users, given that privacy and awareness are rising. Most traditional attribution methods depend heavily on third-party cookies, and those are now losing importance. Cookieless Multi-Touch Attribution (MTA) is the newest way to follow customer journeys privately and practically.

In this article, you will learn about cookieless multi-touch attribution, its importance in marketing today, how to make use of it and best ways to track user activities without cookies.

Table of Contents
1. The Death of the Cookie and the Rise of Privacy-First Tracking
2. What Is Cookieless Multi-Touch Attribution?
3. Why Marketers Need Cookieless MTA
3.1. Compliance With Regulations
3.2. Browser Limitations
3.3. Cross-Device Tracking
3.4. Improved Accuracy
4. Key Methods for Cookieless Tracking
4.1. First-Party Data Collection
4.2. Server-Side Tracking
4.3. Identity Graphs
4.4. Universal IDs
4.5. Contextual Data and AI Modeling
5. How to Implement Cookieless Multi-Touch Attribution
5.1. Audit Existing Tracking Infrastructure
5.2. Adopt Consent Management Tools
5.3. Upgrade to Server-Side Tagging
5.4. Integrate First-Party Data Sources
5.5. Build or Integrate Identity Resolution Capabilities
5.6. Leverage Machine Learning for Attribution Modeling
5.7. Test, Measure, and Optimize
6. Best Practices for Tracking User Journeys Without Cookies
6.1. Focus on First-Party Relationships
6.2. Enable Login-Based Interactions
6.3. Consolidate Data Silos
6.4. Be Transparent About Data Use
6.5. Optimize for Mobile and CTV
6.6. Invest in Clean Room Technologies
7. Tools for Cookieless Customer Journey Tracking
7.1. Google Analytics 4 (GA4)
7.2. Segment (by Twilio)
7.3. Tealium
7.4. Snowplow Analytics
7.5. LiveRamp
7.6. Adobe Experience Platform
7.7. Piwik PRO
Conclusion

1. The Death of the Cookie and the Rise of Privacy-First Tracking

For several decades, digital advertising relied on the strength of cookies. Because of them, marketers could watch user behavior across different websites, create customer profiles, and link conversions to those profiles. At the same time, privacy laws like the GDPR, CCPA, and ePrivacy Regulation, as well as browser changes (Safari’s Intelligent Tracking Prevention and Google removing third-party cookies in Chrome), have had a big effect. To ensure privacy and compliance, marketers should implement strategies that track user journeys differently than when cookies were used.

2. What Is Cookieless Multi-Touch Attribution?

Cookieless Multi-Touch Attribution (MTA) means marketers assign credit based on touchpoints in a user’s path that do not rely on third-party cookies. Instead of relying on cookies in user browsers, it uses other data sources and identifiers to present a complete overview of user behavior with a brand on different platforms. Using cookieless MTA lets companies measure the success of their marketing campaigns within privacy rules.

3. Why Marketers Need Cookieless MTA

Since privacy is becoming more important online, marketers have to adjust their ways of tracking customer journeys. With Cookieless MTA, accurate and respectful tracking can be done throughout the entire user experience. That’s why marketers are including it more in their current advertising strategies.

3.1. Compliance With Regulations

Based on privacy rules such as the GDPR, CCPA, and ePrivacy Directive, companies have to receive consent before collecting user information. If companies do not comply, they could be fined a lot and see their reputation with consumers drop. Instead of using cookies, cookieless MTA depends on first-party data and legal tracking to help marketers follow regulations and measure results from campaigns.

3.2. Browser Limitations

At present, Safari, Firefox, and Google Chrome block third-party cookies automatically. As a result, tracking cookies are no longer effective. Therefore, now, first-party data and alternative optimal identifiers will help MTA marketers track user activities and ensure there is no loss of data due to browser privacy changes.

3.3. Cross-Device Tracking

Brands are accessed by consumers widely, including on phones, tablets, desktops, and even TVs that are connected to the internet. Traditional cookies remain on a single browser and are not accessible on other devices. To address the problem, marketers rely on identity resolution, login information, and combined profiles to better show the process users go through on different devices.

3.4. Improved Accuracy

You can delete cookies, stop them, or experience issues with how they function. Alternatively, cookieless MTA relies on both definite techniques (registered users) and statistical methods (how users behave and the setting) to provide a better assessment. Thanks to these models, noise and errors are reduced, resulting in improved data and a fair view of the role of each touchpoint in making a conversion.

4. Key Methods for Cookieless Tracking

Marketers are using privacy-friendly solutions that function like third-party cookies to support cookieless multi-touch attribution. The goal here is to collect data correctly and still get a good picture of user behavior in different places and on different devices.

4.1. First-Party Data Collection

Directly from users comes first-party data using owned websites, apps, and email services. If users give consent, businesses can collect and use their behaviors and preferences to create detailed profiles. The use of this data is central to personalized marketing approaches and helps guide effective attribution models that don’t need outside tracking.

4.2. Server-Side Tracking

Data collection moves from the user’s browser to the server in server-side tracking. By using this approach, we don’t have to worry about browser rules and can enhance both data security and accuracy. As a result, brands can oversee their data collection from start to finish, avoid losing sensitive details because of users blocking ads or cookies, and ensure they don’t break any privacy laws.

4.3. Identity Graphs

An identity graph combines data points such as email addresses, device IDs, and phone numbers into a single, unified customer profile. This enables consistent user recognition across platforms and devices. With cookieless tracking, identity graphs are essential for maintaining accurate multi-touch attribution, especially in cross-device and omnichannel journeys.

4.4. Universal IDs

Universal IDs like Unified ID 2.0, ID5, and LiveRamp IdentityLink support replacing third-party cookies with approved identifiers that follow privacy rules. By using these IDs, your system can keep track of users as they navigate from one platform to another and ensure their privacy is protected in the process.

4.5. Contextual Data and AI Modeling

When there is no personal identifier, we study device type, the place of the search, the time, and page content through machine learning. With the help of AI, it is possible to understand user behavior and assign credit to marketing interactions depending on how much a user is likely to be engaged, as a safe and smart form of attribution.

5. How to Implement Cookieless Multi-Touch Attribution

Switching to a cookieless way of working with MTA needs careful attention to strategy. Tracking must be restructured, and businesses must focus mainly on their data while adopting advanced methods to correctly monitor and analyze how customers interact.

5.1. Audit Existing Tracking Infrastructure

First, analyze the way tracking is currently deployed in your business. Find all the places where Internet users interact using third-party cookies. By performing this audit, you will know what upgrades are most important, decide on a roadmap to cookieless solutions, and focus on your attribution goals.

5.2. Adopt Consent Management Tools

Thanks to consent management platforms (CMPs), you can collect and handle user preferences openly. A CMP follows privacy guidelines worldwide, so you can correctly collect first-party data. When consent comes first, people can trust your usage of data, and you can continue to collect and use it in the long run.

5.3. Upgrade to Server-Side Tagging

You should try server-side tagging with tools like Google Tag Manager Server-Side. As a result, you can decide which data is shared and how it will be managed. It boosts how your site operates, protects data from disappearing on the client’s machine, and makes it possible to integrate with modern tools that don’t rely on cookies.

5.4. Integrate First-Party Data Sources

By linking your CRM, email, customer support, and app, you create one central data ecosystem. Lumping this information together improves your attribution models, increases the effectiveness of personalization, and helps your team choose marketing actions relying on a complete picture of customers.

5.5. Build or Integrate Identity Resolution Capabilities

You can resolve identity by using your tools or following the identity resolution service of companies such as Neustar or LiveRamp. With these platforms, you can link scattered customer actions by using persistent identifiers, so you can attribute them across various channels and gadgets without cookies.

5.6. Leverage Machine Learning for Attribution Modeling

Reliable models based on AI can uncover touchpoints despite not knowing who the user is. With their ability to process large amounts of data, probabilistic models can predict where users see ads, which is very useful for data-friendly tracking and instant adjustments.

5.7. Test, Measure, and Optimize

Cookieless attribution should always be adjusted and managed continuously. Try to attribute sales by comparing linear, time-decay, or custom algorithmic versions of A/B test models. Monitor how your partners perform and keep improving your strategy to ensure you always give the correct credit for conversions.

6. Best Practices for Tracking User Journeys Without Cookies

Shifting to cookieless tracking means redefining how we engage users and collect data. These best practices ensure ethical, accurate, and effective user journey tracking without sacrificing privacy or performance.

6.1. Focus on First-Party Relationships

Develop lasting relationships with users by providing things in return, for example, tailored content, loyalty perks, or unique offers. A strong relationship with the first party helps boost conversions and lets you rely on attribution and personalization with no cookies.

6.2. Enable Login-Based Interactions

Suggest that users use account logins to sign in on all their devices. Since the identifier doesn’t change, users can be followed from one session or device to another. Persistent, user-approved tracking tools rely on using login-based strategies.

6.3. Consolidate Data Silos

Make it possible for information from marketing, sales, and customer service to be mixed and used together. Having all customer information together in a Customer Data Platform (CDP) makes profiling easier, improves segmentation, and makes it simple to measure user activity on multiple channels.

6.4. Be Transparent About Data Use

Being open about your practices is more important than ever without cookies. Explain to your users what happens to their data once it is collected and how you keep it secure. Allow users to change their data preference settings easily and quickly from their dashboards.

6.5. Optimize for Mobile and CTV

Since you can’t rely on cookies in mobile apps and on CTV, use SDK-based tracking or device identifiers instead. Be sure your attribution models keep up with these quickly growing channels, as they’re often where people start or finish their journeys.

6.6. Invest in Clean Room Technologies

Data clean rooms help partners safely collaborate through the analysis of anonymized data. They make it possible to apply advanced attribution modeling and transfer data safely in regulated industries.

7. Tools for Cookieless Customer Journey Tracking

Tools in the martech space are finally keeping up with new, cookieless ways to track attribution. The following are a few platforms that help marketers follow users’ journeys and don’t rely on cookies from third parties:

7.1. Google Analytics 4 (GA4)

GA4 is built to operate in the cookieless world of tomorrow. It relies on machine learning, events, and first-party data to offer a clear picture of user journeys. Adjustments can be easily made to GA4, and it matches well with Google’s wider set of services for in-depth attribution.

7.2. Segment (by Twilio)

Segment works like a data connector, gathering, organizing, and sending your company’s first-party data to the needed marketing tools. It tracks server-side events, resolves customer identities, and lets you build your marketing on unified customer data.

7.3. Tealium

The platform comes with both tag management and a CDP from Tealium. It allows you to collect information behind the scenes, merge user information, and act on feedback in real-time, all without breaking privacy laws worldwide.

7.4. Snowplow Analytics

A solution that you own and can manage in any way you choose. The Snowplow platform lets you record data for each event on the server and allows you to analyze live behavior automatically without leveraging cookies sent by third-party companies. It suits companies willing to design their cookieless data system.

7.5. LiveRamp

The platform LiveRamp offers is IdentityLink, a powerful solution for resolving data identities. It allows for the transfer of user data from one device to another, helping brands identify which users they should credit with the impact of ads. The integration network supports both online advertisers and publishers.

7.6. Adobe Experience Platform

Using Adobe’s technology, marketers can track customers with no cookies, seeing real-time profiles, using AI for meaningful insights and resolving identity issues. With Adobe’s suite, it safeguards accurate attribution and allows effortless usage across all types of marketing channels.

7.7. Piwik PRO

The Piwik PRO analytics suite is built to give maximum priority to compliance. Users can be tracked without cookies by design, and the program lets marketers store, manage, and access sensitive customer data in industries with strict regulations.

Conclusion

Relying on cookieless multi-touch attribution is ahead of the curve since it fits with new expectations about privacy and changes in technology. With first-party data, using server-side tracking and relying on AI in modeling, marketers can discover plenty of information about users’ journeys and the impact of their campaigns.

Now that traditional tracking methods no longer work as well, companies should switch to cookieless multi-touch attribution, find the right tools, and use best practices for following users’ journeys.

Visit Our SalesMarkBlog Section to Uncover the Sales Strategies That Ignite Your Sales Journey!

Explore the 2025 ROI battle: Intent Data Platforms vs. Traditional Lead Generation. Uncover which approach drives better results for modern marketers.
B2B marketing relies on generating leads, as these leads fill sales pipelines and help the business to grow. Cold calling, sending out mass emails, and taking part in trade shows are traditional ways marketers use to find new customers. Yet, since how customers buy has become more sophisticated and internet-based, intent data platforms now play a major role. They look at users’ online actions to spot those interested in what you offer, allowing you to target them more precisely. This article looks at how ROI between these two approaches differs, with intent data being a main factor in changing lead generation results.
Table of Contents
1. What is Traditional Lead Generation?
2. What are Intent Data Platforms?
3. ROI Comparison: Intent Data Platforms vs Traditional Lead Generation
4. Lead Generation Strategies in 2025
5. The Role of Intent Data in Improving Lead Generation ROI in 2025
Conclusion

1. What is Traditional Lead Generation?

Traditional lead generation is the term given to the established ways marketers attract and find new customers. To prospect, some companies use cold calling, send emails to a big group, go to trade shows, and buy lists with lead information from other companies. For decades, researchers have used these strategies to reach many businesses and gain recognition in the market.
In cold calling, the sales team gets in touch with potential customers to encourage them to go ahead with their services. Email blasts reach a wide audience with advertising messages in the hope of creating new leads. At trade shows, companies can meet and connect with people, but the possibility of contacting pre-built lists through purchase is also available.
Scalability and a reliable history are the two main advantages of traditional lead generation. Companies can target many users and create a constant supply of leads. Moreover, various businesses have developed their own knowledge and systems based on these practices.
Still, there are serious drawbacks to this technology. Traditional approaches have low success rates since many of the contacts are not interested. With the passing of time, these payments increase because the mail recipients become less engaged and more likely to unsubscribe. Using these techniques can also result in drawing poor leads, which wastes time and effort from the sales team.

In 2025 and beyond, organizations are experiencing difficulty with traditional ways of lead generation due to ROI problems. Increased costs for marketing and buyers not responding to simple sales pitches both lower the level of efficiency in the industry. Therefore, a lot of marketers are looking for effective ways to use data and target specific audiences to increase profits.

2. What are Intent Data Platforms?

With intent data platforms, marketers can spot the behavioral signals of people interested in a product. Intent data platforms use data collected from what potential buyers do online instead of sending out advertisements like traditional lead generation.
Intent data covers data collected from a prospect’s digital activities, for example, visiting websites, downloading content, searching online, and interacting on social media. Marketers use the signals to know where a prospect is in the buying cycle and how serious they are about the purchase.
You can find three types of intent data.

• First-party intent data is gathered when people visit websites and interact with a company’s CRM platforms.
• Second-party intent data: Provided to businesses so leads can be enriched.
• Intent data from third parties is gathered from various online sources and with the help of intent data providers.

Managing leads with intent data helps marketers approach interested prospects more accurately and boosts the use of resources. This means the audience stays active, and the resulting leads are better.

In 2025 and beyond, these platforms now include more AI and machine learning, allowing for immediate analysis and future insights. Integrating these tools into CRM and marketing automation features gives sales and marketing teams an advantage in acting fast and effectively.

Intent data has changed the way businesses find leads by approaching more targeted and focused on how buyers act and look for solutions.

3. ROI Comparison: Intent Data Platforms vs Traditional Lead Generation

Marketers consider ROI to be the most important metric while considering lead generation approaches. ROI in lead generation is figured by looking at how much revenue these leads bring in as compared to the entire cost of collecting them. Measuring cost per lead (CPL), conversion rates, speed of sales, and true customer value are crucial for lead generation.
Furthermore, because of their broad approach, passing on marketing material to everyone often leads to big expenses. Labor costs, the purchase of details, and participating in events can make the CPL significant. Furthermore, a small percentage of contacts convert to customers, as many are not really interested or simply unqualified. Therefore, sales take more time to complete and cost businesses more to attract new customers.
Unlike the others, intent data platforms boost lead generation by investing in leads who exhibit characteristics of an imminent purchase. By reviewing online actions like content use, search history, and how frequently users interact, the platforms find prospects that are most likely to become leads. When you target marketing more precisely, waste goes down and qualified leads rise.
Several case studies from 2025 highlight this.

• After adding intent data to its marketing process, the B2B SaaS company experienced a lower CPL by 30% and saw a 25% rise in conversions within six months.
• Using intent data, this technology vendor improved sales speed by 20%, bringing the sales cycle down from 90 days to 70 days.
• Account-based marketing (ABM) campaigns using intent data resulted in twice the amount of engagement in selected accounts compared to using just lists.

Even with these advantages, the traditional approach to lead generation is not outdated. It is still important for bringing awareness to brands and attracting many viewers. Still, its ability to generate returns declines as there is more noise in the market and buyers have higher expectations.

For the strongest outcome, use intent data platforms for personalized and prioritized approaches, yet continue with regular marketing to reach and support a large audience over time. With both approaches, workers can process as quickly as possible.

4. Lead Generation Strategies in 2025

As of 2025, lead generation strategies have responded to how buyers now act and the latest tech developments. Marketing today stresses using analytics in combination with intent data, AI, machine learning and automation to build more effective and automated campaigns.
Previously, predictive analytics and intent data were separate, but now they are often used together. Historical and current information on behaviors is used by these tools to predict the best prospects for sales staff to act on. It improves the process of qualifying leads compared to using demographic or firmographic data only.
It’s now common for successful lead generation to rely on engaging people via multiple channels. Prospects can connect with a business through email, social media, websites, video, chatbots, and events. They collect information from various channels, so marketers can tailor their campaigns based on how active prospects are in each place.
Both real-time information and automation are crucial today. Thanks to marketing automation, you can automatically send targeted messages whenever prospects behave as though they are ready to buy. When someone downloads a whitepaper or visits the pricing pages more than once, automated messages can be sent to them,m or salespeople can immediately contact them.

Still, old advertising channels are effective and often improved by adding data insights. Trade shows, webinars, and outreach are key elements in growing relationships with leads. Intent data ensures that you choose the right event participants and individualize your approach depending on the audience’s interests.

Also, 2025 regulations and guidelines expect marketers to be clear about their uses of intent data and to receive consent from buyers while offering something valuable. When this balance is present, the brand becomes trustworthy, benefiting the company’s efforts to secure leads in the long run.
Combining technology, data, and people, the lead generation process for 2025 smoothens out marketing efforts and helps companies achieve the best possible ROI.

5. The Role of Intent Data in Improving Lead Generation ROI in 2025

Through intent data platforms, companies can ensure they capitalize on their lead generation efforts by choosing the leads most likely ready to buy. In contrast to previous strategies that deal with all leads the same way, intent data lets sales and marketing target those most likely to buy.
Marketers can spend their budgets more effectively this way. Reducing spend on unqualified leads helps channels to focus on interested leads, which results in more deals and greater revenue.
Aligning sales and marketing relies heavily on intent data. With up-to-date information on prospects’ interests, marketing can hand active leads to sales teams just when the prospects are highly receptive. This close coordination allows processes to happen faster and results in more successes.
Personalized messages can be delivered to a large number of people. Because of intent data, marketers have more opportunities to adjust offers, email messages and advertising to fit each person’s unique needs. When you use personalization, customers engage more and develop trust in your business, leading to a better ROI.

Furthermore, intent data platforms make it possible for companies to react swiftly to happenings in the market. When the interests of buyers change for any reason, marketers are able to quickly modify their campaigns and sales strategies to address these opportunities.

With digital noise on the rise, companies will need intent data more than ever to stand out and capture leads effectively. If intent data is used well, businesses have better leads, deal closures happen more swiftly, and they are more competitive, resulting in better lead generation returns.

Conclusion

Intent data platforms help to produce better ROI than traditional lead generation, which is achieved by using stronger personalization, targeting, and better matching of sales efforts. Even though traditional techniques work, using intent data is necessary for companies to continually grow in today’s competitive market. As AI becomes more advanced and privacy-friendly data sharing is made easier, lead generation strategies will be further perfected by using intent data in the future.

Visit Our SalesMarkBlog Section to Uncover the Sales Strategies That Ignite Your Sales Journey!

Explore 15 top intent data platforms to enhance B2B lead generation, uncover buyer intent, and drive targeted marketing for better conversion and revenue.

Businesses operating in today’s competitive B2B market gain crucial lead generation advantages through precise and timely decision-making.
With intent data platforms, sales and marketing teams acquire the ability to detect active product and service research behavior from potential customers, thus obtaining valuable strategic advantages.
Behavioral signals from these tools yield insights about both potential buyers’ timing of interest along with their specific subject matter, allowing organizations to make contact before rivals become involved..
This article explores the 15 best intent data platforms that can supercharge your B2B lead generation, boost engagement, and shorten sales cycles. Whether you’re a startup or an enterprise, the right platform can fuel your pipeline growth.

Table of Contents
1. Understanding the Role of Intent Data Platforms
2. 15 Best Intent Data Solutions for B2B Lead Generation and Sales Teams
2.1. Bombora
2.2. 6sense
2.3. Demandbase
2.4. ZoomInfo Intent
2.5. LeadSift (now part of Foundry)
2.6. Slintel (by ZoomInfo)
2.7. True Influence
2.8. SalesIntel
2.9. Cognism
2.10. RollWorks
2.11. G2 Buyer Intent
2.12. VisitorQueue
2.13. KickFire (now part of Foundry)
2.14. Intentsify
2.15. Metadata.io
Conclusion

1. Understanding the Role of Intent Data Platforms

Intent data platforms extract digital information signals that reveal potential buyers’ subject focus along with their product or service interest.
Websites, review platforms, and online behavior serve as sources for digital signals that include keyword searches, content consumption, and competitor research. This development brings critical advantages to business-to-business sales and marketing groups.

With intent data, teams eliminate random efforts by directing their resources toward accounts moving through the buying process. The high level of intelligence allows tailored outreach that produces stronger conversion rates and delivers improved returns on investment. The platforms combine naturally with CRM systems, ABM tools, and lead generation tools for B2B to provide a combined actionable view of prospect behavior.

Businesses can reduce the sales cycle and match marketing initiatives with sales teams by using real-time data combined with predictive analytics to identify high-intent accounts. The best intent data solutions for B2B lead generation and sales teams are transforming into essential operational requirements now that complex buying journeys have emerged.

2. 15 Best Intent Data Solutions for B2B Lead Generation and Sales Teams

2.1. Bombora

Bombora is a premium B2B intent data provider that focuses on providing precise and actionable data from Company Surge analytics. It identifies buying intent by monitoring the consumption of content through a vast B2B content consumption network called Bombora Data Co-op. It helps the users know which companies are really interested in the topics related to their solutions so they can prioritize their leads and approach them.
It is easily connectable with other CRMs and marketing platforms from Salesforce, Marketo, and HubSpot. The positive aspects are strong B2B purchase signals as well as CRM/ABM compatibility. Cons include higher cost when used by a team of fewer members, and also, when used by novices, they may take some time to master them. Thus, the pricing is unique depending on the amount of information that is being processed and the number of users in the company.
Bombora is most effective for mid- to large B2B businesses that are looking for increased opportunities to link sales and marketing for timely intervals, driven by data connections with active and engaged prospects to drive down sales cycles and increase conversion rates.

2.2. 6sense

6sense is an AI-based intent data platform that refines B2B lead generation through blending intent data, predictive analytics, and in-depth account engagement data. It identifies anonymous buying behavior, finds hidden opportunities, and knows which accounts are most likely to convert, thus enabling the sales and marketing teams to reach out to the intended buyer at the right time in their buyer’s journey.
Such provisions as account scoring, sales alerts, and keywords make 6sense effective in establishing highly targeted connections and better pipeline development. Advanced features make it perfect for large corporations, yet it has a high learning curve, and per-quote pricing is not beneficial for startup companies.

2.3. Demandbase

Demandbase boasts a powerful ABM and intent data system that allows B2B enterprises to find and sell to accounts that are ready to buy. It provides users with a rich prospect profile incorporating firmographic, technographic, and behavioral data. It also provides account-based marketing and enables marketers to monitor the behavior of their buyers in real-time.
On a positive note, the application has numerous features that may be very useful, but setting them up may be a challenge, and it is not cheap. Hence, it is best used by organizations that have highly developed ABM programs seeking to maximize the value of lead nurturing by refining targeting and integrating with a CRM tool. Best for: strategic ABM-driven B2B enterprises.

2.4. ZoomInfo Intent

ZoomInfo Intent combines high-quality intent data with one of the largest B2B contact lists out there, which helps to pinpoint up-to-date leads. It means that it provides what prospects are researching and when through examining behavioral signals of more than 300,000 websites.
It is most useful for ZoomInfo customers because of its native integration with the toolset. The total cost, however, can increase significantly if more features are added. Proprietary for B2B audiences, which considers enhancing the quality of intent insights with a set of actionable ones within the familiar environment. Best for: Teams currently leveraging ZoomInfo and wanting to augment their ability to identify and reach prospects based on their intent data.

2.5. LeadSift (now part of Foundry)

LeadSift, which is now a part of Foundry, utilizes intent data from various sources like social media, forums, blogs, and content networks. This allows the sales and marketing departments to identify potential customers long before they complete a form or otherwise interact with the company. It provides daily leads of qualified prospects and easily integrates into CRM systems, offering pure sales triggers and information.
The strengths are the exclusivity of the data, the practical methodologies to interpret the data, and the quick and accustomed coverage of the customer’s needs. The cons are that it has less data than some of the other companies out there. Pricing is fair with a focus on SMB subscription and usage patterns. It is more suitable for businesses that have a high number of leads to generate at comparatively lower costs.

2.6. Slintel (by ZoomInfo)

Slintel, which now operates as a subsidiary of ZoomInfo, uses technographic data and purchase intent data to help B2B companies find promising leads. It follows buying signals by the technologies that the prospects are likely to use and their stage in the buyer’s journey. These insights offer real-time information in terms of the contact details and help to identify the right decision-makers in a shorter time. Strengths: efficient use of technographic segmentation and competitive intelligence.
The cons are that it is limited to a restricted area of focus and can be somewhat overlapping with some of the murmurs from ZoomInfo. The basic modules of ZoomInfo are not priced individually, and the pricing is coordinated with the plans used by the consumer. Peculiarities of the analysis include the identification of the buying stage of consumers, integration with CRM systems, and contact updates. Best for tech-focused B2B prospecting strategies.

2.7. True Influence

True Influence is a comprehensive intent data solution that provides both multi-channel data and contact-level information to B2B marketing organizations to identify fence-sitters. Its flagship IntentBase platform scans large-scale publisher ecosystems to identify content consumption matching areas of interest to business. For the business teams, we have scalable enterprise solutions and features such as data enrichment, contact scoring, and account profiling.
One of the notable advantages is its high accuracy, but the design of the program itself may cause difficulties sometimes for the users, and their training might be necessary. On the aspect of pricing, Huawei sends out a quotation depending on the usage volume of the software. Best for: enterprise-level marketing teams, specifically on the B2B side, that are involved in sophisticated, multi-step demand generation processes.

2.8. SalesIntel

SalesIntel gives you both buyer intent insights and human-verified contact data to make sure B2B sales and marketing organizations are working with high-fidelity leads. It works in partnership with Bombora, which strengthens its intent data offering and helps it remain a reliable source.
Technographics, CRM syncing, enrichment, and intent are notable attributes, as they are all significantly crucial for outreach. That is considerably less than its leading competitors, such as ZoomInfo, but it offers such benefits as 95% accuracy and verified data. Pricing is well-regulated according to the feature required and the number of leads needed from the site. Best for: B2B sales teams that require accurate and credible contacts as well as better targeting.

2.9. Cognism

Cognism is a GDPR-compliant company that focuses on providing intent data, contact details services, and sales intelligence, primarily aimed at B2B companies that sell to EMEA and North America markets. As a result, its clean, compliant datasets are loaded with buying signals, firmographics, and trigger alerts to enable the teams to work at the right time.
The onboarding process is seamless, and there are robust privacy features, which are useful for markets with standard compliance requirements. However, it is not very rich in APAC, and its intent features are not fully developed. Pricing is done according to quotation, and different companies can avail themselves of a 15-day free trial version. Best for: companies targeting services and solutions specific to business-to-business selling that give preference to data privacy and obscure lead sources.

2.10 RollWorks

RollWorks, a NextRoll subsidiary, provides in situ account-based marketing (ABM) and intent data to empower B2B organizations to target account prospects more effectively. Combined with the firmographic, technographic, and behavioral data it provides to clients, RollWorks helps to deliver account-based advertising to build pipeline velocity. It can also work with CRMs and MAPs to ensure that the campaigns are aligned with the sales objectives effortlessly.
On the plus side, strong features cover the mid- to late funnel, but the reporting and time to optimize a campaign can be a bit challenging for users. Pricing is relatively low at the starting point with the ‘Starter’ plan; however, more advanced features are available for enterprises on a quote basis only. Perfect for B2B marketing teams and industries engaged in hard ABM and large-scale build-out of display advertising.

2.11 G2 Buyer Intent

G2 Buyer Intent allows B2B organizations to leverage the data and insights of buyers who are interested in their products on G2. It shows the company that has explicitly visited your profile or any specific pages, such as category pages or competitor listings, which is highly useful for SaaS and tech companies. G2’s insights are derived from actual in-market behavior, thereby involving less risk compared to the sample-based satisfaction scores; the insights are also meant to seamlessly slot into sales and marketing processes.
Still, it is only useful for companies listed in G2 and might not provide much information beyond technology fields. A pricing model has been tied to the G2 Premium Profile, while extra data options are also available. Recommended if you’re in the technology niche, looking to engage your audience at the late stage of the buyers’ journey.

2.12 VisitorQueue

Using IP tracking, intent data, and enhancements to prospect records, VisitorQueue uncovers which companies are coming to your site even if they’ve never completed a form. It is especially useful for businesses of all sizes and mid-scale B2B businesses interested in monetizing anonymous traffic. It is straightforward, compatible with CRMs, and provides great support.
It is not as in-depth and complex as some enterprise-focused tools, but it is way cheaper and much easier to use. Plans start at just $31/month, scaling based on traffic volume. VisitorQueue is ideal for budget-conscious B2B teams seeking to convert passive website visitors into qualified leads.

2.13. KickFire (now part of Foundry)

KickFire focuses on IP-to-company intelligence, catering to B2B marketers who want to know not just which companies are visiting their site, but also if they did not fill out a form. Firmographic data integrated with real-time intent data ensures that your teams cannot only nurture the warm leads but also uncover new ones.
The platform stands out in the recognition of accounts in real-time and easily integrable APIs for ABM tools + CRMs. Although the setup can be an optional solution, it may omit several constant connections, such as those from a remote user or a small business sharing an IP address. KickFire, being a pay-per-data-usage product, is ideal for companies that are interested in outbound marketing with website analytics to convert the anonymous traffic to leads.

2.14 Intentsify

It is worth mentioning that Intentsify offers multi-source intent intelligence to offer a rich account view of intent across the funnel. It compiles the best available data feeds and applies machine learning results to identify accounts that are truly interested in your products. Furthermore, Intentsify provides managed services to bring this data to life in executable marketing solutions. Several merits of Hootsuite Amelia make it rather suitable for large companies with large-scale needs for intent marketing to cater to.
Since the pricing is not transparent, it might need a large overhaul by small business organizations. Notable features include cross-channel analytics, custom processes, and campaigns. Intensify is one of the most all-encompassing solutions for B2B organizations that are placing a particular focus on the quality of pipeline and growing revenues from marketing efforts.

2.15 Metadata.io

Metadata.io is a great martech solution that leverages the power of intent data to drive and improve the demand generation strategies, mostly using paid media. It links with intent providers, such as Bombora, to identify prospective clients, and it executes campaigns to generate more high-quality leads.
Users get a chance to work with a set of features, including automated A/B testing, built-in CRM synchronization, and ROI reports. However, it has a slow onboarding and is better suited for mid-market to enterprise-level companies, starting from $3950/month.

Conclusion

Exploring the right intent data platform for your business can boost the B2B lead generation efforts and reach the right audience at the right time. Ranging from AI- and ML-generated insights to account-level indications and website visitor identification, the solution set provides the insights required to gain an edge over the competition.
Each of the 15 intent data platforms that are described in the article has its own strong sides—it may be wide integration capabilities, relatively low prices, or top-notch analytics.
Consider size, goals and objectives, and budget when deciding which option is best suited for your needs. Once you have the right intent data platform set up, the B2B sales and marketing teams will be able to close more business in less time.

Visit Our SalesMarkBlog Section to Uncover the Sales Strategies That Ignite Your Sales Journey!

Discover the benefits and drawbacks of Multi-Touch Attribution models. Learn how MTA tracks touchpoints and helps optimize marketing performance.

Explore how personalization and automation are transforming B2B marketing in Asia. Discover key trends driving growth and engagement across the region.

The evolution of B2B marketing in Asia has been dramatic over the past few years. The current business evolution toward digital transformation enables two primary trends that shape powerful marketing strategies based on personalization and automation. These trends, driven by technological developments together with changing customer expectations, have transformed how B2B companies approach prospect interactions and relationship development and market expansion throughout the diverse Asian regions.

Table of Contents:
1. The Digital Acceleration of B2B Marketing in Asia
2. Why Personalization Matters More Than Ever
2.1. Rising Customer Expectations
2.2. Data Availability
2.3. Localization Needs
3. Automation: Scaling Marketing Efficiency
4. The Synergy Between Personalization and Automation
5. Regional Trends and Insights
5.1. India: Automation at Scale
5.2. China: Data-Driven
5.3. Japan: Precision and Trust
5.4. Southeast Asia: Mobile-First Marketing
5.5. South Korea: Tech-Savvy and AI-Driven
5.6. Singapore: Hub for Martech Innovation
Wrapping Up!

1. The Digital Acceleration of B2B Marketing in Asia

Asia experienced a tremendous advance in digital technology because of the pandemic. McKinsey reports that Asian customer interactions moved forward three to four years through digital transformation within a brief period of 2020. B2B marketing teams gained the opportunity to utilize technology for precise targeting activities and meaningful engagements because of this acceleration. Businesses adopted virtual communication and content marketing alongside webinars and social selling, which triggered the importance of automation tools and personalized strategies for better return on investment and converting leads. Digital transformation became an imperative for all businesses that need to compete effectively in today’s adaptable B2B market that depends on immediate hyperconnectivity between companies.

2. Why Personalization Matters More Than Ever

The extensive cultural and linguistic diversity throughout Asia makes personalization an absolute requirement for business success. Businesses operating across countries like India, China, Japan, Singapore, and Indonesia face varied buyer behaviors, preferences, and decision-making processes. The use of standard solutions has become completely inadequate. Key drivers of B2B personalization in Asia:

2.1. Rising Customer Expectations

Organizational buyers expect customized servicing experiences identical to those they get as consumer clients. The essential elements of successful differentiation include personalized content together with pertinent recommendations tied to situational messages.

2.2. Data Availability

Marketers now obtain hyper-personalization capabilities through enhanced Customer Data Platforms (CDPs) and CRM systems, which provide detailed behavioral as well as firmographic and transactional data.

2.3. Localization Needs

Asia-based personalization requires localization through the modification of linguistic elements and cultural elements in addition to language adaptation. A marketing message effective in Singapore needs completely new strategies to succeed in Japanese and Vietnamese markets.

3. Automation: Scaling Marketing Efficiency

Fast-paced B2B operations in Asia require the two critical success factors of personalization for relevance and automation-driven efficiency and scalability. Marketing automation tools provide companies with the capability to automate repeated operations while delivering sequence-based lead development combined with targeted messaging throughout email, social media, and chat communications. The Asian market adopts email drip campaigns that deliver personalized content through buyer stage advancement, as well as AI-powered chatbots for mobile-focused support and automated lead priority systems that base scores on user behavior.

Thanks to HubSpot, Marketo, and Zoho platforms, many organizations choose these platforms because they enable complex task simplification and automation management. B2B marketing professionals in the region leverage automation to handle their manual tasks and achieve real-time engagements and lead management improvement, together with better return on investment and flexible multichannel and multi-language capabilities. The increasing need for speed and scale requires organizations to implement automation as their fundamental tool for achieving highly effective marketing efforts that preserve high-quality standards.

4. The Synergy Between Personalization and Automation

Integrating personalization with automated functions produces a substantial force that leads B2B marketing to become more intelligent. Market automation creates the ability for marketers to tailor campaigns during mass deployments, which leads to relevant messages without reducing operational speed. Singapore-based SaaS providers can use user behavior tracking to initiate automated emails tailored to specific industries that offer demo services. The manufacturing firm in India employs automation tools to deliver personalized white papers that address the specific requirements of their event participants according to their job positions and business sizes. Customer engagement achieves higher conversion rates, and more targeted relationships develop because of this combined approach.

5. Regional Trends and Insights

Each Asian market presents unique challenges and opportunities when it comes to personalization and automation.

5.1. India: Automation at Scale

The B2B market in India shows strong interest in marketing automation to process large lead volumes effectively and enhance their targeting capabilities. Market automation tools such as WhatsApp automation, along with CRMs and email workflows, help execution teams maximize their outreach capabilities in both SMBs and enterprises. The implementation of marketing automation at scale remains limited by two main obstacles: poor customer data quality and connectivity problems with outdated systems in place.

5.2. China: Data-Driven

Personalization The distinctive Chinese digital system operating through WeChat and Baidu forces marketers to develop data-driven B2B methods that specifically adapt to local market preferences. AI-powered segmentation within social CRMs allows companies to deliver highly customized marketing initiatives according to Chinese business traditions. Platform fragmentation, together with strict data privacy laws, makes it difficult for automation systems to become integrated with larger marketing ecosystems, which would enable personalization consistency across all channels.

5.3. Japan: Precision and Trust

The Japanese B2B marketing environment centers around building trust between companies while focusing on delivering high-quality relationships that extend across prolonged periods. Companies use deep insights to create customized content that fulfills cultural expectations in personalization strategies. The tactic of selective automation adoption exists to assist human operations instead of taking over their responsibilities. B2B marketing success in Japan depends on thought leadership content, account-specific webinars, and precise segmentation techniques.

5.4. Southeast Asia: Mobile-First Marketing

Businesses in Indonesia, Vietnam, and the Philippines have started adopting mobile-first B2B tactics since their populations embrace smartphones. Marketers utilize mobile CRMs together with chatbots and localized messaging apps to automate their operations of lead generation and customer engagement. Rapid growth in Southeast Asia, together with its multiple languages, presents obstacles for maintaining uniform personalization and automation through standard frameworks across the entire region.

5.5. South Korea: Tech-Savvy and AI-Driven

South Korean B2B marketers demonstrate strong embracing behavior toward AI and automation through their implementation within CRM systems and chatbots, as well as predictive analytics capabilities. Digital maturity of the audience drives B2B marketers to focus on immediate personalization and automated content recommendation systems. South Korean markets need continuous technological advancements along with strong localized strategies to succeed under prevailing data privacy regulations and technology innovation standards.

5.6. Singapore: Hub for Martech Innovation

Singapore stands as a leading technology and business center through which Asia’s B2B martech market follows its lead. Modern companies are using automation to create multichannel marketing initiatives along with account-based marketing and artificial intelligence for personalization purposes. Global customer bases allow personalization efforts to extend across different regions because of strong backend data systems. Businesses face two key obstacles when they aim to merge high-tech innovation with market privacy rules and deliver targeted content throughout multiple regions.

Wrapping Up!

The digital expansion of Asia will lead B2B marketing practices throughout the region toward greater intelligence, human-based approaches, and automatic response strategies. Personalization alongside automation moved from desired features to basic requirements in business strategy. Achieving the right equilibrium between automation controls and personalized authenticity stands as the essential principle. Business success in Asia’s dynamic B2B market goes to those marketers capable of leveraging data while employing advanced technology, while maintaining regional sensitivity.

Visit Our SalesMarkBlog Section to Uncover the Sales Strategies That Ignite Your Sales Journey!

Learn how to leverage automation to personalize video content for your APAC B2B audience and boost engagement, relevance, and ROI across diverse markets.

As cookies disappear, context takes the spotlight. Here’s why relevance > identity in modern ad strategies.

The digital ad landscape is in the midst of a seismic change. The gradual destruction of third-party cookies, fueled by increased regulation and changing consumer attitudes, is no longer an abstract future—it’s already underway. And yet, most brands are still wedded to identity-driven targeting models that don’t reflect the real world.

So the question is not what fills the void left by cookies—we already know. It’s whether C-suites are prepared to adopt contextual advertising as something other than a last resort, but as a fundamental growth strategy in a privacy-first era.

Table of Contents:
1. Letting Go of the Cookie Crutch
2. Context Gets Smarter—And More Strategic
3. Relevance Beats Identity
4. Regulation Sparks Innovation
5. Walled Gardens Aren’t the Answer
6. First-Party Data Alone Won’t Save You
7. The AI Advantage
8. Strategic Questions C-Suites Must Ask
Rethinking What Matters

1. Letting Go of the Cookie Crutch

Google’s staged removal of third-party cookies in Chrome, slated to finish later in 2025, is the last installment in a long-overdue process. Apple, Firefox, and regulators have long since moved on. But many organizations have not. Why?
Because cookies were supposed to be precise. They constructed an empire on behavioral information, following individuals from site to site with unnerving specificity. But that accuracy had a cost—regulatory danger, consumer distrust, and technical vulnerability.
Now, brands are faced with the unpleasant reality: clinging to cookies is no longer safe or successful. The smarter question is: what targeting tactic delivers when identity data runs dry?

2. Context Gets Smarter—And More Strategic

Contextual advertising has been around for a while. But nowadays, it’s not merely about keywords on a page anymore. In 2025, sophisticated AI, Natural Language Processing (NLP), and real-time content classification support a degree of semantic targeting equal to behavioral models, without violating privacy.

Today’s contextual engines examine tone, sentiment, visuals, and even cultural subtlety. Platforms such as Seedtag and GumGum, for instance, are using AI models trained on multimodal data to make ads appear where they’re extremely relevant and brand-safe. These models take into account the emotional gravity of content rather than simply the subject matter, providing resonance over pure reach.
And it succeeds. As a 2025 IAB Europe report reveals, contextual campaigns now achieve 23% higher average engagement compared to cookie-based campaigns. That’s not only ethically right—it’s strategically right.

3. Relevance Beats Identity

There remains a prevalent assumption that personalization is about knowing the user’s identity. But contextual turns that thinking on its head. What if what matters most about the user is their environment and state of mind rather than their name and past?

Consider The Washington Post. By removing third-party cookies from a vast majority of its ad inventory, the newspaper concentrated on in-session contextual targeting through its own Zeus platform. The outcome? Improved viewability, stronger brand lift, and a 34% boost in cost efficiency for flagship campaigns in 2024.
This movement prompts executives to question: do we actually need to understand who an individual is, or merely what they are interested in—today?

4. Regulation Sparks Innovation

Data privacy frameworks around the world are tightening. Europe’s Digital Markets Act, California’s CPRA, and Brazil’s LGPD aren’t barriers—they’re indicators. Privacy alignment will be a requirement for international ad scale by 2025, not a compliance box.

Forward-thinking companies are leveraging this pressure as fuel. They’re auditing martech stacks, investing in consent-based experiences, and constructing contextual pipelines that scale without personal identifiers. As Gartner’s recent report points out, “privacy by design” is no longer a constraint but a leading driver of adtech innovation.

5. Walled Gardens Aren’t the Answer

Brands are resorting to Big Tech ecosystems, spending more money on Google, Meta, and Amazon. While these platforms provide scale and deterministic targeting, however, they limit access to data, creative control, and boost acquisition costs.

Contextual advertising on the open web provides a choice, transparency, control, and competitive bidding environments. In a time when media diversity is important, being dependent solely on walled gardens is perilous. Contextual provides brands with the means to regain agency and relevance, especially in mid-funnel and awareness strategies.

6. First-Party Data Alone Won’t Save You

There’s a rising story that first-party data is the silver bullet. And it’s important, but it can’t scale by itself. Not all brands have logged-in environments or deep engagement loops.

Contextual advertising bridges that gap. It serves as a scalable layer of relevance where first-party signals are weak or absent. The future is hybrid models—contextual + consented data + AI-driven creative—that adjust in real time to user journeys.

7. The AI Advantage

Contextual strategies are being rewritten by generative AI. With generative AI, marketers are able to generate dynamic, contextually aware creatives that keep pace with the emotion and content of a page in milliseconds. Not only does this drive engagement—it drives better brand perception.

Picture a fitness brand serving up hydration-oriented creative on a marathon news page while also highlighting recovery supplements on a sports injury handbook—all fueled by contextual AI, without user tracking.

8. Strategic Questions C-Suites Must Ask

Executives need to transition from tactical to strategic when considering contextual advertising:

Do we have the technical infrastructure in place to handle real-time contextual delivery?
Are our media KPIs still based on cookie-era metrics?
Are we approaching privacy as a limitation or as a differentiator?
By 2026, IDC expects 70% of digital ad budgets to be spent on privacy-aligned solutions, with contextual expected to grow at an 18% CAGR.
Rethinking What Matters
Contextual advertising is not nostalgia—it’s strategic flexibility. It provides relevance without trade-off, trust without tracking, and performance without reliance.
The winners in a post-cookie future will be those that redefine context not as a contingency, but as fundamental infrastructure. Because in a privacy-first world, knowing the moment is more important than pursuing the identity.

Visit Our SalesMarkBlog Section to Uncover the Sales Strategies That Ignite Your Sales Journey!

Explore best practices for ethical data management in today’s digital world—build trust, ensure compliance, and protect user privacy effectively.

Data-driven innovation alongside strategic decision-making requires ethical data management approaches to be noncompromisable in modern times. Protecting the integrity of data, along with privacy and maintaining trust, has become essential because digital environments dominate how organizations and individuals conduct business. The responsible use of data through ethical practices both maintains its proper utilization and safeguards personhood rights while blocking improper access.

The alignment of data strategies with ethical principles represents a core basis for digital citizenship, which ensures brand credibility in the interconnected digital world of today.

Table of Contents:
1. The Essence of Data Ethics in APAC
2. Five Best Practices for Ethical Data Management
2.1. Transparency and Consent
2.2. Data Minimization and Purpose Limitation
2.3. Security and Confidentialityg
2.4. Accountability and Governance
2.5. Fairness and Non-Discrimination
Conclusion

1. The Essence of Data Ethics in APAC

The APAC functions as a digital powerhouse because it contains more than 60% of the global population. This rapid digitalization of India, China, Singapore, and Australia has generated massive daily data production for both personal and B2B enterprise needs.

Looking at the intensity of the expansion of data creates ethical dilemmas about consent protocols, security measures, and algorithmic fairness, together with usage responsibility. This situation calls for data ethics laws across APAC countries; however, in the 21st century, these laws differ widely, looking at the varying public and understanding the levels of legal development needed among nations.

For instance, the PDPA framework in Singapore, the Personal Information Protection Law (PIPL) in China, the Digital Personal Data Protection Act (DPDP) in India, and the Act on the Protection of Personal Information (APPI) in Japan stand as the leading data privacy standards. On the other hand, numerous nations are still developing comprehensive guidelines that work best in creating a data secured enviroment.

Digital growth in the APAC region requires public trust through an accountable and innovative data management system that balances ethical conduct with technological development.

2. Five Best Practices for Ethical Data Management

2.1. Transparency and Consent

The practice of ethical data handling depends on transparency because organizations need to show users exactly which data they gather and why, alongside the intended usage. User trust automatically dissolves when terms are not openly displayed, so users require access to informed consent, which grants control over their data while also allowing for penalty-free choice.

Organizations need to maintain their ethical principles by using clear terms in privacy policies while using OneTrust or TrustArc consent management platforms for permission handling and by keeping users informed about all changes to data handling rules.

2.2. Data Minimization and Purpose Limitation

The process of data collection should be limited to essential information because both increased security threats and possible ethical violations result from excessive data gathering when information goes unused or unsecured. Accurate data usage demands purpose limitation, which restricts data utilization to its original use and prohibits all secondary uses unless consent is reobtained.

Organizations need to do data audits to check the validity of their data collection while employing Symantec DLP and Microsoft Purview, as these tools control and establish data storage guidelines based on business needs and regulatory requirements.

2.3. Security and Confidentiality

Data privacy and integrity depend on strong security measures as these constitute basic ethical commitments to protect data from illegal access attempts. The increasing number of cyber threats makes encryption together with anonymization practices essential along with robust access control systems. Secure access becomes possible through Zero Trust Architecture implementations, which authenticate every device and user, and by using VeraCrypt and BitLocker tools to protect data with encryption.

Multiple-factor authentication (MFA), together with role-based access controls (RBAC), creates additional security levels, and periodic penetration tests and security audits help businesses discover and fix weaknesses ahead of time.

2.4. Accountability and Governance

B2B organizations need to establish specific roles for data management to maintain ethical practices because defined responsibilities support the efficient handling of datasets. Data Protection Officers (DPOs) need to exist according to GDPR and PDPA requirements together with data governance standards that include COBIT or DAMA-DMBOK and continuous evaluation from internal boards for data-driven project ethics. Providing consistent data ethics and compliance training to employees creates two benefits: first, it promotes responsible practices across different organizational levels, and second, it establishes accountability throughout the organization.

2.5. Fairness and Non-Discrimination

The increasing use of AI and machine learning systems for critical decisions, including credit scoring and recruitment, requires immediate focus on ensuring fairness while reducing biases. The ethical requirement for data management needs ongoing inspection to detect and solve biases present in datasets and AI code. Performing Algorithmic Impact Assessments (AIA) stands as a best practice before AI system deployment, and data scientists should utilize tools from IBM AI Fairness 360, Google’s What-If Tool, and Fairlearn and promote team diversity to obtain varied perspectives during model development.

Conclusion

Organizations need to adopt ethical data management practices since they represent a fundamental need in modern digital environments. The combination of ethical principles with data practice alignment creates sustained trust for businesses, which results in increased resilience and sustainable innovation, especially within APAC dynamic markets. A transparent and accountable data management approach combined with fairness principles allows organizations to secure their data strategies for the future while building a responsible digital environment.

Visit Our SalesMarkBlog Section to Uncover the Sales Strategies That Ignite Your Sales Journey!

The Asia-Pacific (APAC) market presents strong competition and diverse regional preferences, which makes businesses need to center their operations on customer needs to achieve market leadership. The optimization of customer journeys stands as an essential factor that drives customer engagement, develops brand loyalty, and creates more conversions. Organizations need to develop a data-driven approach because consumers behave differently throughout the APAC region. Companies using Customer Data Platforms (CDPs) achieve a complete view of client interactions, which allows them to build fluid, personalized interactions.
In this article, we will understand how APAC companies can use top CDP solutions to properly optimize their customer journey paths.

Table of Contents:
1. The Importance of Customer Journey Optimization in APAC
2. Key Challenges in Customer Journey Optimization in APAC
2.1. Fragmented Data Sources
2.2. Diverse Consumer Behavior
2.3. Regulatory Compliance
2.4. Technology Gaps
2.5. Omnichannel Complexity
3. Leading CDP Solutions for APAC Businesses
3.1. Twilio Segment
3.2. Adobe Experience Platform
3.3. Salesforce CDP
3.4. ActionIQ
4. Steps to Implement a CDP for Customer Journey Optimization
4.1. Define Business Objectives
4.2. Assess Data Sources and Integration Needs
4.3. Ensure Data Quality and Compliance
4.4. Select the Right CDP Solution
4.5. Develop Customer Segmentation Strategies
Conclusion

1. The Importance of Customer Journey Optimization in APAC

Conducting customer journey optimization enables businesses to offer appropriate interactions that arrive at optimal times while being personalized according to each customer’s needs.
The APAC region witnesses fast digital transformation, thus leading consumers to demand integrated omnichannel interactions. Organizations that optimize their customer journey paths achieve better user satisfaction levels, which produce both higher customer retention along with sales revenue expansion.
Small businesses face unique challenges in the APAC digital market because they operate across mobile-first economies while dealing with high social commerce adoption together with multilingual customer bases.

Organizations that neglect customer journey optimization will lose customers to businesses that deliver superior experiences to their consumers. The implementation of CDPs allows organizations to merge diverse touchpoint data for accurate segmentation purposes, better targeting effectiveness, and enhanced customer interactions.

2. Key Challenges in Customer Journey Optimization in APAC

Companies face multiple hurdles when optimizing customer journeys throughout the APAC region because of its distinctive market conditions.

2.1. Fragmented Data Sources

Several data streams exist in APAC, including WeChat for China, Line in Japan, and WhatsApp in India. Even e-commerce platforms such as Lazada, Shopee, and Tokopedia interact with their customers through data. However, multiple data silos make it challenging to create a single customer view, which harms personalized service effectiveness.

2.2. Diverse Consumer Behavior

The region’s various cultures and spoken languages create obstacles for personalization strategies across APAC. The purchasing values of Japanese consumers center on high-quality products along with trusted brands, but Indonesian customers prioritize low prices linked to their strong interest in social commerce platforms. An effective customer engagement system requires a complete understanding of consumer-specific details.

2.3. Regulatory Compliance

Marketing approaches come under direct influence from the multiple strict privacy laws that exist in the market. The PDPA of Singapore demands direct customer permission before collecting data, whereas the PIPL of China establishes strict standards for international data transmission. The laws require businesses to maintain compliant operations for personalised delivery.

2.4. Technology Gaps

Smaller business organizations throughout Southeast Asia face difficulties in accessing AI-based analytics along with marketing automation capabilities, which hinders their ability to enhance customer journeys. Traditional Vietnam retailers maintain manual operational approaches that harm their ability to create seamless omnichannel service.

2.5. Omnichannel Complexity

Customers use various channels for their interactions, which makes delivering seamless interactions extremely challenging. Customers who begin their shopping journey on Instagram in India will find product information there before turning to Flipkart reviews before completing the transaction at stores. Sophisticated technologies with coordinated operations are essential to build the required integration between these customer touchpoints.

3. Leading CDP Solutions for APAC Businesses

​CDPs function as vital tools for Asia-Pacific businesses, which maximize customer data collected from multiple sources to personalize marketing and enhance experience quality for customers. The top five CDP solutions that APAC businesses use include:

3.1. Twilio Segment

Companies can use Twilio Segment as a developer-oriented Customer Data Platform, which helps them process and maintain data from multiple locations with advanced functionality. The system offers comprehensive API solutions alongside real-time event tracking and flexible schema structures to meet the requirements of high-volume processing needs.

This platform combines strong privacy and security features to deliver the unification of data for streamlined compliance in addition to its user interface. Although most businesses need specialized technological knowledge to maintain the system after setup, this system presents obstacles to technical novices. Twilio Segment provides free basic usage, but its paid plans begin at $120 per month and provide custom enterprise pricing.

3.2. Adobe Experience Platform

The powerful Adobe Experience Platform functions as a data management system that builds time-sensitive, customized interactions for multiple touchpoints. The AI-powered Adobe Sensei system gives businesses real-time insights to effectively handle customer data so they can run omnichannel initiatives. Real-time customer profiles join cross-channel journey orchestration with advanced data governance tools as essential platform features.

The solution blends with Adobe products in a seamless integration for detailed management of customer experience through powerful artificial intelligence and machine learning features. The product remains unattainable for small businesses because it comes with a high price tag and requires specialized technical installation. Customers must request price details as Adobe Experience Cloud bundles its pricing within packages.

3.3. Salesforce CDP

Salesforce CDP unites with the Salesforce Customer 360 suite to deliver businesses integrated customer data visibility throughout the Salesforce platform. This system targets companies that aim to perform experience personalization at scale through its AI-driven data analysis, which unites cross-cloud information while performing identity-based segmentation in real time. The core benefits of this solution are the natural integration of Salesforce products alongside superior data segmentation while maintaining user-friendly features for current Salesforce system operators.

The platform presents three main restrictions through its restricted inter-operational flexibility with non-Salesforce systems and high deployment expenses and user requirements of Salesforce professionals. Custom pricing exists for bigger implementations, while $12,500 monthly represents the minimum price for up to 50,000 profiles.

3.4. ActionIQ

ActionIQ functions as an enterprise-level Customer Data Platform (CDP) that makes data accessible for business teams while freeing them from extensive dependency on IT support. The platform utilizes AI-powered customer analytics, and its advanced segmentation system works together with omnichannel communication management alongside a business self-service interface. ActionIQ provides data democratization capabilities along with cloud, on-premise, and hybrid deployment flexibility, strong security measures and compliance features.

Small businesses might find the complexity beyond their capabilities and will need to pay more for this solution, which also presents a challenging learning experience for users without technical backgrounds. Every business solution receives an individually generated offer by ActionIQ sales professionals for pricing based on unique requirements.

4. Steps to Implement a CDP for Customer Journey Optimization

Businesses will establish successful CDP implementation by following the following process:

4.1. Define Business Objectives

Organizations need to select their main targets between enhancing personalization features together with retaining more clients and creating the best omnichannel consumer journeys. The selection of proper CDP features, together with integrations becomes easier when objectives are established clearly.

4.2. Assess Data Sources and Integration Needs

The evaluation should focus on analyzing the present data available through CRM software along with social media tools and web analytics systems. Select a CDP that can connect without issues to existing systems for maintaining continuous data movement.

4.3. Ensure Data Quality and Compliance

A necessary care for data health involves the removal of redundant information alongside obsolete records. Governance protocols should have strong security measures in place to meet the data compliance requirements throughout APAC.

4.4. Select the Right CDP Solution

Assess available CDP solutions through a combination of their capabilities to scale, integration of AI technology, system simplicity, and specialized features for industry applications. Safety testing of the system should begin before final deployment.

4.5. Develop Customer Segmentation Strategies

AI analytics should be used to create customer segments according to purchasing behavior and other customer characteristics and buying intentions. Team up personalized marketing strategy with segment-based approaches for better campaign efficacy.

Conclusion

Organizations in the dynamic APAC market must optimize the way customers journey through their operations. CDPs support businesses by uniting customer information, which enables personalized connection points across various interaction touchpoints. Companies activating best-in-class CDP solutions along with structured execution methodology will find growth opportunities and achieve digital-first economy competitiveness and improved customer loyalty in the APAC market.

Visit Our SalesMarkBlog Section to Uncover the Sales Strategies That Ignite Your Sales Journey!