Data reveals nearly all marketing organizations have integrated AI into operations, creative and analytics, but few have embedded it into business functions that drive revenue

Accomplished technology marketing leader joins Nintex to accelerate growth in agentic business orchestration

Veteran growth, commerce, and digital strategy executive joins an advanced analytics company to accelerate go-to-market scale and strategic partnerships

Evergreen Digital Media Corp. (EDM), a premier operator of digital signage and retail media networks, and Adwave Digital Inc. (Adwave), a technology company that operates an AI-powered advertising platform, have finalized a strategic partnership in which EDM will provide capital to facilitate the continued development of Adwave’s AI platform. EDM will also receive a preferred licensing agreement to the platform as part of the agreement.

Adwave’s WaveRunner platform buys and runs ad campaigns across streaming TV, Google, Meta, Reddit, and the web from a single daily budget, optimizing placement using a business’s own site data, without requiring an agency or separate accounts for each channel.

This is EDM’s third strategic investment in the past year, but a different type of deal. The earlier investments brought new screen networks into EDM’s fold. In this partnership, EDM obtains rights to run Adwave’s AI ad-buying technology directly, without taking on another network to operate.

“Adwave brings a level of talent and technical knowledge in the advertising AI space that’s rare to find,” said Don Winfrey, CEO of Evergreen Digital Media Corp. “We’re excited to learn from this team as we bring that expertise into our networks.”

“EDM has built something real in the DOOH space, and we’re glad to be working alongside a team with that kind of reach,” said David Naffis, CEO of Adwave. “We’re looking forward to what this partnership produces.”

Recognition Highlights WisdomTree’s Leadership, Innovation, Commitment to Financial Advisor Success

Marketing and e-commerce teams can now generate and edit images with OpenAI’s latest image model — without leaving the workspace where they already produce AI video.

Predictive vs. Descriptive Analytics is not an either-or choice. Learn how leaders can connect historical context with forecasting for better decisions.

Historically, data-driven leadership was predictably a process that involved reviewing quarterly data, determining what was successful, discussing what was not, and making changes to the approach. The retrospective orientation is driven by descriptive business intelligence – the answer to the most fundamental business intelligence question: What happened?

That question is still relevant today. However, when conditions in the market – customer behavior, costs, demand, competition- change more quickly than planning cycles, customers must be informed not just of what has happened, but of what is likely to happen next. With the need to predict what might occur next- a trend that has consistently been growing in the business agenda- leaders are finding themselves increasingly responsible for developing predictive analytics.

This is a false dichotomy between past and future.

However, no organisation is more forward-looking by giving up on historical analysis. They get better and better when they link the two together. Descriptive analytics is what the business knows, while predictive analytics takes that know-how and forecasts what is likely to happen next. The true strength is when both are involved as part of a shared decision-making process.

Table of Contents:
Hindsight Still Has a Job to Do
The Problem With the “Predictive Leap”
The Real Advantage Is the Feedback Loop
Predictive Is Not Always Better
What Leaders Should Change
The Better Question Is Not Predictive vs. Descriptive

Hindsight Still Has a Job to Do

The difference between descriptive and predictive analytics goes beyond a simple “past versus future” definition.

Descriptive analytics converts business data from the past into a clear picture of what has occurred. It aggregates data from various systems, including ERP, CRM, financial, and operational databases, to uncover trends, gauge performance, and set standardized metrics. If leaders are asking how descriptive analytics can help them understand what has happened to their organization, the answer is in context. Any company would have to understand its present situation, as well as how it got there, before it could make any sense of the improvements/deteriorations it is experiencing.

Learning from that, Predictive Analytics follows. Uses statistical models, machine learning, and pattern analysis of past and present data to calculate the probability of future events. Rather than just saying customers are churning, a predictive model could tell you that of the already-existing customers, which ones are exhibiting high-risk customer churn behavior.

It is, therefore, not whether you select one way over another but rather what question each of the ways answers. Descriptive analytics answers the question: What is this organization? Descriptive analytics answers the question that is: What is this organization? Predictive Analytics attempts to identify patterns in that evidence and make predictions about the next thing that may occur. One offers a point of reference and the other a glimpse into the future.

The Problem With the “Predictive Leap”

One of the biggest errors that many companies make in implementing predictive analytics is approaching it as the next software system to be bought instead of an extension of the company’s data discipline.

While leaving scattered source data in place, they invest in models and machine learning platforms or data science teams. This is, in fact, a fundamental issue; models learn from their information input. Technically, the models can be very sophisticated, and if the underlying data are incomplete, inconsistent, and not well-contextualized, one of these forecasts can be very confident but is still incorrect.

The challenge is further enhanced if there are changes in market conditions.

A model that is mainly based on the same economic conditions might not be reliable in situations of sudden changes in consumer behaviour, price, supply chain, or interest rates. What has happened in the past can be of service, but perhaps cannot be used to describe the situation the business is in.

Hence, in order to ensure that predictive analytics remains effective, it must be continuously validated. Leaders should know not only what a model suggests but why the assumptions upon which it is based are still valid. While the mathematics behind a forecast may be correct, the conditions that gave rise to those patterns can change, and the forecast may fail in this sense.

The Real Advantage Is the Feedback Loop

Best analytics practices integrate descriptive, predictive, and operational systems, not as three distinct phases.

Imagine a B2B business that is keen on cutting down the customer attrition rate. A descriptive analysis may show that there is a higher rate of churning customers whose use of the platform drops after their third month. That historical trend provides the business a helpful starting point.

This pattern can then be used in live accounts to detect those displaying similar indicators. Rather than allow those customers to leave, account teams have the opportunity to reach them with focused retention messaging.

The process should not end at the time of the intervention, however. The organisation should document customer responses, what interventions were successful, and what accounts churned despite them. Those effects form new evidence. They reinforce the descriptive basis and provide more meaningful information for future predictive models.

The process repeats itself: understand what happened, figure out what could have happened, do something about it, observe the results, and learn from that to better inform future decisions.

That’s when analytics goes beyond reporting and predicting. It becomes a learning characteristic of the organization.

Predictive Is Not Always Better

A general sentiment the predictive analytics become the predictive decision makers. It does not.

When an organisation has ample historical data, has similar patterns, and decisions that require a best guess and statistical prediction, they are especially helpful. Examples include supply chain planning, inventory forecasts, equipment maintenance, credit risks, and customer attrition, as these signals and outcomes can be seen over time by a business.

There are other decisions that are far more unpredictable.

If a company ventures into a wholly new market, implements an unfamiliar business model, or considers a very atypical acquisition, then the past may be of limited use. In such cases, good descriptive analysis will be more useful than prediction. Leaders must grasp the market and incorporate that data with industry knowledge, experience, and qualitative judgment.

It also goes for any decisions that are driven in a legal, geopolitical, cultural, or organizational way. Because a probability score is associated with a percentage does not mean it is a substitute for executive judgment.

The goal should NOT be to get the most out of predicting in the organization. It should be to see how prediction can enhance a decision and how it can lead to false confidence.

What Leaders Should Change

To transition to predictive analytics, more needs to be done than simply adopting new technology. It demands a new mindset when it comes to decisions.

Leaders must allow themselves to get used to probabilities, not certainty from all models. Executives should not ask a data team to show that an outcome will happen, but instead determine how the organization should respond if it reaches a reasonable probability. That shifts the focus of analytics from an explanation exercise to one focused on managing risk and opportunity.

In parallel, businesses shouldn’t feel tempted to overlook their descriptive bases. Poor avoidance of data discipline can’t be made up for by predictive models; hence, it is important to maintain clean historical data, consistent definitions, and reliable reporting.

This also implies that model performance should be reviewed and not validated once. However, as customers’ behavior, market opportunities, and business goals evolve, companies must decide if their models are generating valuable signals or merely repeating a pattern from a bygone world.

The Better Question Is Not Predictive vs. Descriptive

The key issue is whether an organisation has established a platform where evidence from the past is used to establish expectations for the future, future expectations drive action, and action in the past produces results that adjust future expectations.

That’s what it takes to be analytical.

Descriptive analytics provides context for leaders to grasp the business past. Predictive analytics enables them to get ready for where it might go. Both are necessary, and neither should be used alone.

The value of analytics is not that analytics makes you know more about the past or predict the future with greater certainty; the organizations that get the most benefit from data will be the ones that link the two. It is the result of better decision-making with both.

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

New health and life sciences practice debuts AdherenceIQ, an AI-powered platform that predicts patient adherence risk

Medication nonadherence costs the U.S. healthcare system as much as $300 billion annually. Despite significant investments in awareness, patient acquisition, and new prescription generation, life sciences companies struggle to identify which patients will start/discontinue therapy and understand the emotional barriers driving those decisions.

Response Media today announced the launch of RE: HEALTH, a specialized health and life sciences practice built to help pharmaceutical and health brands close that gap.

Backed by decades of healthcare marketing expertise, RE: HEALTH combines behavioral science, privacy-compliant AI and advanced analytics to help brands identify the emotional barriers to treatment and translate that intelligence into engagement strategies that improve adherence, persistence and TRx growth.

“Medicine is an emotional decision but the industry has marketed it as a functional one,” said Josh Perlstein, Response Media CEO. “We believe there is a smarter approach, and it begins with focusing on the human behind every treatment.”

With the launch, the company is introducing AdherenceIQ, a proprietary, AI-powered behavioral intelligence platform that predicts and addresses therapy adherence risk before drop-off occurs.

Built on published adherence science, AdherenceIQ identifies the emotional and functional barriers preventing patients from starting or continuing therapy, predicts who is most likely to disengage and why, and recommends intervention strategies based on those barriers.

For chronic and rare disease therapies, where adherence and persistence are critical to patient outcomes and commercial performance, AdherenceIQ shifts the focus from measuring attrition to identifying patients at risk of disengaging while there is still an opportunity to intervene.

“Adherence is too often treated as a reminder problem,” said Dr. Alvin Glay, chief strategy officer, RE:HEALTH. “But patients don’t make decisions based on reminders. Concerns about side effects, necessity, distrust, and stigma all shape their decisions. We can now uncover those barriers early enough to intervene in a relevant, human way that not only improves patient outcomes but accelerates TRx growth.”

With over two decades of health tech marketing and communications leadership, Konstantinidis joins to amplify AssureCare’s market momentum, accelerate adoption and extend its presence into new segments.

AssureCare®, a leading AI-powered population health management company, today announced that Kristen Konstantinidis has joined the company as Senior Vice President of Marketing and Communications.

Healthcare organizations are under more pressure than ever to adopt AI-enabled technology that actually delivers results, not just promises them. For too long, healthcare technology has promised interoperability, actionable intelligence, and whole-person care – but too often has delivered fragmented point solutions, disconnected data, and innovation that fails to translate into meaningful action at the point of care. AssureCare has spent years building something different: a platform that connects stakeholders, turns complex data into usable insights, and enables care teams to intervene with clarity, speed, and purpose. Now the company is building the team to make sure the market knows it.

“Kristen has a rare gift for translating complex technology and true healthcare outcomes into ROI-driven success stories that resonate, regardless of the audience – whether that’s a boardroom, policy table, or clinical floor,” said Yousuf Ahmad, President and CEO of AssureCare. “AssureCare is not simply building technology. We are redefining how healthcare organizations identify needs earlier, coordinate care more effectively, and improve outcomes for the people and communities they serve. There’s no one better suited to share that story with stakeholders than Kristen.”

Most recently, Konstantinidis served as Chief Communications Officer at Homeward Health, where she built the company’s communications and brand marketing function – including government relations, positioning for the Rural Health Transformation (RHT) Program, and AI narrative strategy. That experience gives her particular insight into one of the most consequential shifts in healthcare today: the move toward responsible, AI-enabled, proactive care. She brings it to AssureCare to help tell the story of how intelligent technology and compassionate care work together to remove friction instead of adding it, so the people delivering care can stay focused on the people who need it.

“I chose AssureCare because of the combination of an exceptional team, compelling mission, proven technology, and enormous opportunity,” said Konstantinidis. “At AssureCare, AI is not a slogan or a disconnected feature, it is an enabler of better decisions, more efficient care teams, stronger engagement, and measurable outcomes. My job is to make sure the market knows the scale, effectiveness and impact AssureCare makes on millions of lives, and I can’t think of more meaningful work to be part of.”

Small businesses across the United States are increasingly looking for practical and affordable ways to build brand visibility, promote their products, and create professional customer experiences. Printing Limitless is supporting this demand with a broad range of custom branding and printing solutions designed for businesses of different sizes and industries. Through its online platform, the company provides customizable products that can help businesses promote their brands at storefronts, events, trade shows, markets, offices, and other customer-facing environments. Its product portfolio spans Banners, Stands & Displays, Table Covers & Displays, Signs & Decals, Clothing, and other promotional materials.

For businesses seeking cost-effective ways to increase visibility, Printing Limitless offers a variety of Custom Vinyl Banners, Outdoor Banners, Promotional Banners, Retail Banners, Restaurant Banners, and Company Banners. The company also provides display products such as Roll Up Banner Stands, Adjustable Banner Stands, Step and Repeat Displays, Pop-Up Displays, and Sidewalk Signs/Sandwich Boards, giving small businesses multiple options for communicating promotions, services, and brand messages. These products can be used for storefront promotions, grand openings, trade shows, local events, sales campaigns, and everyday business visibility.

Beyond banners and displays, Printing Limitless provides products that help businesses create a more consistent branded environment. Its Table Covers & Displays category includes Premium Full Color Table Covers & Throws, Fitted Table Covers, Convertible/Adjustable Table Covers, and Table Runners, while the Custom Flags category includes Feather Flags, Blade Flags, Teardrop Flags, and Rectangle Flags. Businesses can also explore products such as Custom Canopy Tents, LED Neon Signs, and Marketing Materials to build cohesive branding across physical locations and promotional activities. This broad selection allows small businesses to choose individual products or combine multiple printed elements based on their marketing goals and budget.

Ron David, Operations Manager at Printing Limitless, said, “Small businesses need branding solutions that deliver a professional appearance without making the process complicated or unnecessarily expensive. Our goal at Printing Limitless is to make customized printing accessible to businesses across the USA by providing a wide selection of products and customization options in one place. Whether a business needs a simple banner for a storefront, a branded table cover for a local event, a display for a trade show, or custom flags to attract attention from the street, we want to give customers practical options that fit their individual needs. We are proud to support small businesses as they build stronger and more recognizable brands.”

As part of its current customer offer, Printing Limitless is also providing a limited-time 15% discount on all purchases with coupon code FLAT15. The offer can help small businesses reduce the cost of customized branding materials, whether they are ordering Custom Vinyl Banners, Roll Up Banner Stands, Custom Canopy Tents, Custom Flags, Table Covers, or other promotional products. Printing Limitless continues to focus on combining product variety, customization, and online convenience to help businesses create professional physical branding experiences. With its expanding product portfolio and focus on small-business needs, the company aims to make affordable custom printing solutions in the USA more accessible to businesses looking to strengthen their local presence and connect with customers.