• Predictive AI can anticipate when a customer is most likely to churn and trigger retention campaigns before it happens.
• Generative AI can personalize email content, product recommendations, or even ad creative for each user at scale something manual teams could never achieve.
• Journey orchestration platforms infused with AI can adapt the next best action for a customer as their context changes, rather than locking them into a rigid funnel.

• Customer Data Platforms (CDPs) powered by AI can reconcile identities across multiple touchpoints, resolving fragmented profiles into a single source of truth.
• AI can also cleanse, enrich, and normalize messy legacy data turning previously unusable information into actionable insights.

• Data scientists and marketing technologists will become core to every team, bridging creative storytelling with analytical rigor.
• Copywriters will evolve into AI content strategists, leveraging generative tools to ideate and scale.
• Campaign managers will transition into journey architects, focusing on customer experience orchestration rather than one-off campaigns.

• Trust & Transparency: Customers want to know when they’re interacting with AI, and they expect responsible data usage. Clear disclosure and ethical guardrails are essential.
• Bias in Models: If AI is trained on biased data, it will deliver biased outcomes. Companies must actively monitor, audit, and retrain models to ensure fairness.
• Change Management: Marketers often resist AI adoption because it challenges familiar workflows. The answer is gradual integration, strong governance, and upskilling programs.

1. What does the setup and onboarding process look like for advertisers using Engaged Audience Planning for the first time?

Media planning today is complicated enough, so we’ve made onboarding to Engaged Audience Planning as easy as possible. This process doesn’t require a new workflow or integration; we align with advertisers’ existing planning tools, like those from Nielsen, Kantar Media, or VideoAmp. Clients can see which scenarios offer the best combination of reach, engagement, and cost efficiency — all before a dollar is spent.

Advertisers simply share their existing media plans — including scenarios and metrics like GRPs or CPMs — with EDO. From there, our team maps the plans to EDO’s cross-platform TV outcomes data, calculating engagement rates and outcome efficiency for each scenario. This provides a clear, side-by-side comparison that illustrates how different investment scenarios can result in various combinations of audience impressions and outcomes.

2. EDO has measured over 110 trillion cross-platform impressions — how does this dataset power the predictive models behind the solution?

EDO’s dataset spans every major linear network and a growing number of streamers, enabling us to model how different audiences respond to ads. Our predictive models analyze ad-driven behaviors, such as brand search, website visitation, and LLM chat engagements, which are proven indicators of consumer intent. Using vertical AI to analyze engagement across trillions of impressions and hundreds of industries, we surface meaningful patterns that predict future performance by program, daypart, genre, and more. This enables us to forecast engagement outcomes at scale and optimize our approach toward them before campaigns even begin.

3. Can advertisers using other platforms (e.g. Adobe, etc.) also integrate EDO’s data for unified planning?

Whether it’s Engaged Audience Planning or any other product in our suite, EDO data is designed to be interoperable. Whether a brand is using Nielsen, VideoAmp, Kantar, or agency planning tools from Dentsu, GroupM, or IPG, EDO’s outcome data can be layered onto existing plans with no disruption. We’ve structured Engaged Audience Planning to work flexibly within the tools clients already rely on, often using exported files to match and model engagement outcomes. There’s no need for a formal integration or technical relationship to get started.

4.  In what ways does Engaged Audience Planning support both brand awareness and performance marketing objectives simultaneously?

Traditional audience planning often forces a trade-off between brand reach and performance. With EDO’s data, advertisers no longer have to choose. Our solution helps brands identify plans that deliver both strong audience reach and measurable outcomes. That means marketers can optimize their investments for mid- and upper-funnel KPIs in tandem — a growing priority in convergent TV, where brand and demand goals increasingly overlap.

5. How do you see this tool fitting into or enhancing existing audience segmentation strategies used by brands?

Audience segmentation is essential, but advertisers don’t see the full picture unless they also know how viewers in each audience segment engage with the ads they see. By pairing outcome data with audience targets, EDO adds a crucial layer of intent to segmentation strategies, enabling advertisers to define their audiences and test which environments actually drive those segments to take action. This enables more effective media planning, where audiences are prioritized on both relevance and predicted performance.

6. What message would you give to brands still hesitant to fully embrace data-driven, outcome-optimized planning in a convergent TV world?

The media landscape is only getting more fragmented, and guesswork simply won’t cut it. Brands that embrace outcome-based planning gain a competitive edge — not just in efficiency, but in clarity. EDO helps advertisers make more confident decisions by connecting plans to real consumer behavior. If you’re still relying on audience reach alone, you may be missing the plans that deliver better results for the same or lower cost.

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1. In what ways does combining manual curation with algorithmic ranking influence your approach to customer experience and conversion optimization?

Combining manual curation with algorithmic ranking allows us to strike a balance between creativity and scale. Manual curation allows retailers to highlight seasonal trends, sponsors, editorially chosen features, and other considerations that may not be picked up from an automated algorithm. This is a great addition to the algorithmic ranking that supports the massive scale of infinite searches and the various ways customers express their needs, whether it's finding a specific product or getting help for a unique scenario. This hybrid approach enhances the customer experience by allowing retailers to solve their customers’ needs more accurately and quickly while also reducing the operational overhead of fully manual configurations. We can leverage AI to help us interpret both user intent and business goals, leading to more efficient and effective conversion optimization.

2. How are you addressing the challenge of managing large or frequently changing catalogs, and what operational improvements could you unlock for your business? 

Large, complex catalogs are where accurate and efficient search and discovery becomes really important. The first step in managing large catalogs is making sure they are fully complete and content rich. Every product must have images, descriptions, and translations, or they simply won’t be found or purchased. Next, Algolia focuses on how we can make the catalog better. For example, we can curate and personalize it for specific audiences. This includes layering in rich content such as guides, how-tos and comparisons. Since generating this content is time-consuming and costly, we have given retailers the ability to automatically generate descriptive content using GenAI. And then lastly, make sure everything is operational. We use AI to create and rank content products, create category pages rich in content, and apply image recognition to match products beyond simple metadata. These improvements significantly boost operational efficiency while still elevating the customer experience.

3. How does the ability to personalize search results and category layouts align with your broader personalization strategy across digital touchpoints?

Personalization is most effective when every touchpoint feels relevant and intuitive to the individual, and takes into account who the customer is, their current needs, and informed by recent behavior. By tailoring search results based on behavioral signals, retailers can reduce friction and add true value to a consumer’s shopping experience. Beyond search, personalizing category layouts continues to show a deep understanding of individual preferences. For example, recognizing that one shopper’s “summer look” inspiration will likely be influencing a “back-to-school” wishlist. Beyond making a sale, this personalization builds trust and loyalty in a brand.

4. How are you currently exploring retail media as a revenue stream, and how are you enabling brand placement, sponsored content, or inventory-based monetization? 

We work closely with many customers who are investing in retail media and promote their own brands through sponsored content and strategic placements. Customers also have additional revenue streams by hosting channels. Our approach blends manual input with AI optimization. Creatively, we support the manual curation to ensure that particular sponsors or content types are featured in appropriate locations based on brand relevance. At the same time, we leverage AI within our search systems to rank and feature the most optimal products and content driven by real-time customer behavior.

5. Which departments beyond merchandising—such as content, marketing, or media—could benefit most from a no-code, AI-driven content positioning tool, and how will it shape interdepartmental collaboration?

Beyond merchandising, marketing teams would benefit significantly from the combination of creative freedom and intelligent automation, allowing them to tailor campaigns and promotions while introducing them at scale. UX and customer service teams also benefit and could learn more about the content people consume.

6. How important is it to have a unified tool that supports consistent yet localized product and content presentation?

It is incredibly important. Customers are far more likely to engage with—and ultimately purchase—products and content that feel tailored to their needs, location, and preferences. By leveraging a single platform, retailers can maintain brand integrity and quality while also delivering localized, relevant experiences.

1. What does your approach to real-time personalization different from other CDPs or journey orchestration platforms?

Most CDPs and journey orchestration platforms limit how much data can be used for real-time personalization, often restricting brands to a narrow set of behavior signals and limited customer history. Hightouch removes those limits. Our approach is built around full data access and flexibility, enabling marketers to combine real-time behavioral signals with the complete depth of customer history from the data warehouse. With our new take on same-session personalization, we made it possible, for the first time, to react to in-session activity using the entire customer profile. Whether you're delivering an experience in under a second or orchestrating it over minutes, our real-time product suite is designed to meet the full range of real-time needs with no trade-offs between speed and data richness.

2. Same-Session Personalization is a bold claim. What was the core challenge in marketing that this feature is solving?

The core challenge is relevance in the moment. Without understanding current customer behavior, personalization efforts can create a disconnect between user intent and brand response. Same-session personalization solves this by allowing marketers to react to in-session signals, like product views, cart behavior, or site search, in less than a second. That means offers, messaging, and experiences can adapt as the customer is browsing, not after they've bounced. Our approach to same-session personalization goes one step further, and makes it possible to combine behavior signals with complete customer history in under a second. Brands can interact with their customers as a person, not just a set of digital behaviors.

3. Many CDPs force marketers to choose between speed or historical depth. How do you remove that trade-off?

Hightouch is uniquely positioned as a Composable CDP, which means we use the data warehouse as the source of truth for rich customer profiles, while also integrating real-time event streams. This approach means marketers don’t have to sacrifice depth for speed. You get the historical context of warehouse data and the in-the-moment context of behavioral events. It’s not about choosing between the past or the present. With Hightouch, you get both.

4. How do you handle identity resolution in same-session scenarios where the user might not yet be logged in?

We can use anonymous identifiers to stitch session activity to a profile. Whenever an anonymous user authenticates or provides identifying information, we can retroactively connect their session data to their historical profile in the warehouse, and be ready to address that user’s anonymous identifiers in the future as well. This enables persistent, privacy-safe personalization that respects user consent, while still delivering highly relevant experiences in the moment.

5. What’s your take on how AI and decisioning engines are collapsing the gap between insight and action?

AI is transforming marketing from reactive to predictive. With tools like Hightouch’s AI Decisioning, we’re enabling marketers to operationalize insights the moment they emerge. Rather than waiting for analysts to surface trends or build segments, AI models can evaluate user behavior and context in real-time. AI Decisioning constantly experiments and continuously improves delivery based on the results of each experiment. The result is personalization that’s not just fast, but smart—driven by data, governed by logic, and scaled through automation. Even with this rapid iteration, it’s also really important to surface key insights back to marketers, so they can improve their overall strategies and create more effective content and campaigns.

6. How do you envision yourself evolving to support marketers as zero-party and consent-driven data become the new norm?

Hightouch is built on privacy-first principles. As the industry shifts toward zero-party and consented data, our composable architecture gives brands full control over what data is collected, how it’s used, and where it’s activated. We’re also investing in features that help marketers surface and act on self-reported preferences in real time, whether that’s through consent banners, preference centers, or in-product feedback. The purpose of personalization is to create connections with people, and that starts with trust. With Hightouch, security, privacy, and trust are not an afterthought; they are core components of our architecture and company culture.

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1. How important is a diverse background in sectors such as healthcare, financial services, and technology when considering a candidate for a fractional CMO role?

Finding a fractional CMO with expertise in your company’s sector is ideal. While there's always a learning curve when someone new joins, a CMO who already understands the industry can cut that curve in half. They can focus immediately on the business model, differentiators, strategic vision, and goals rather than starting with industry fundamentals.

Sector-specific knowledge enables the fractional CMO to create impact from day one. However, if your business operates in a niche space and relevant experience is hard to find, the next best option is someone with strong B2B or B2C experience that aligns with your model.

2. What strategies will you employ to ensure seamless integration of leadership with your current marketing department and overall company culture?

Integration starts with the fractional CMO spending time with the CEO and president to understand the organization’s mission, vision, and values. They should ask insightful questions about what defines an ideal team member and what signals a poor cultural fit.

The executive should also share their leadership style and work with senior leaders to assess how that approach aligns with the marketing team and broader structure. If the company uses frameworks like EOS or Radical Candor, the CMO should either be familiar or open to learning.

One-on-one interviews with marketing team members are critical. These conversations reveal career paths, roles, communication styles, and challenges. The CMO needs to understand strengths and development areas—both soft and technical. Tools like Predictive Index can support this process by surfacing team dynamics quickly.

3. How will you leverage data-driven insights to inform your organization’s marketing strategies and business decisions?

In the first month, a fractional CMO should conduct a thorough review of year-over-year metrics and industry benchmarks. This includes evaluating website performance like traffic patterns, bounce rates, session duration, subscriber growth, and form conversions. It’s also important to assess how recent algorithm changes may have impacted traffic.

Channel performance is another priority. Social growth, engagement, and the role of each channel in driving qualified traffic and leads should be reviewed. Paid media efforts need analysis as well, especially cost-per-lead trends and lead quality over time.

If the company attends trade shows, measuring ROI for each event will help determine future participation. And with AI changing how people discover content, growing an opt-in database of leads and subscribers is more critical than ever. Funnel conversion metrics help guide decisions on where to optimize.

Once this data is reviewed, the CMO can prioritize initiatives that align with strategic goals. Without accurate, timely insights, marketing strategies lose their power.

4. What factors influenced your decision to incorporate fractional marketing leadership into your organization’s growth strategy?

CEOs often bring in a fractional CMO when they realize marketing has potential to drive growth but isn’t yet delivering. Marketing has become more complex, and existing team members may be skilled doers but not strategic leaders who can optimize technology, people, and process.

The decision is sometimes driven by competitor activity when others gain visibility through branding, websites, thought leadership, or speaking engagements. This creates urgency to improve market presence and perception.

Meanwhile, the cost of a full-time CMO, typically $250,000 to $300,000, can be out of reach. A fractional leader provides senior-level insight at a more reasonable investment, helping companies move forward without overextending.

5. In what ways do you expect a fractional CMO to contribute to your organization’s long-term growth and competitive advantage?

A fractional CMO should be measured against clearly defined metrics from day one. Most companies want a clear brand strategy and a go-to-market plan that improves awareness, positioning, and market share.

Results should include a healthier pipeline, faster lead velocity, and better close rates—all driven by focused messaging and campaign execution. Some fractional CMOs also support product or service launches, with success tracked by market traction and sales performance.

Others are hired to explore new verticals or markets that offer better growth than current segments. Expanding into new areas can boost long-term growth and create lasting competitive advantages.

6. How will the addition of a fractional CMO influence your company’s future marketing hires and department structure?

Once companies see the value of fractional marketing leadership, they often expand the approach. Many go on to hire full fractional teams—experts from the same firm who collaborate under shared goals and tested processes.

This model works well for companies that want to scale quickly without the burden or lag of internal hiring. These teams bring specialized skills and cutting-edge tools, offering instant impact.

Hybrid structures are also popular. One or two full-time employees, typically a coordinator or manager, are paired with a fractional CMO and a tailored team of generalists and specialists. This approach delivers both continuity and access to senior-level strategy, all while remaining agile and efficient.

Debra Andrews is the President and Founder of Marketri, a strategic marketing consulting firm helping mid-sized B2B businesses modernize their marketing functions, adopt AI with intention, and build stronger relationships with their clients and teams

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