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AI Search Optimization Can't Wait: Why Marketers Must Adapt Now

AI Search Optimization Can't Wait: Why Marketers Must Adapt Now

marketing 20 Nov 2025

Global State of Ecommerce 2025 report found that 11.4% of retail traffic from ChatGPT converted to sales, compared with 9.3% for paid search and 5.3% for organic search.

While good SEO contributes to AI referrals, the winners are not always the same. For example, Ally Bank gets more referral traffic from ChatGPT than traditional banks. Why? Because ChatGPT prioritizes well-reviewed, user-friendly products, and Ally Bank consistently performs well in organic sources like Reddit and review sites that ChatGPT favors. So far, there is no ChatGPT advertising that would allow brands to buy a place at the top of the banking recommendations.

Think conversation, not conversion

While high conversion rates for AI are interesting, we can’t just focus on clicks that drive traffic with GenAI the same way we do with search. Traditionally, users who entered search queries were looking for links to click on. That’s changed as AI summaries become common on search engine results pages, driving up zero click behavior. It’s changed even more with GenAI, where links are presented as footnotes to a chatbot’s answers.

That makes it doubly important to understand the types of conversations consumers are having with AI engines. Through repeated prompts, answers, and follow up questions, they are learning about your brand and products through pre-digested AI summaries of your content in combination with independent news, reviews, and social posts that either support or undermine your marketing efforts.

That’s how the AI decides whether your website, blog post, or product page is worth linking to – and how the consumer decides if the link is worth clicking on. Instead of clicking, they might research your brand further through conventional search – about 95% of ChatGPT users also continue to use Google – but only if the AI answer motivated them to learn more. Getting traffic as a result of these interactions is important but so is the opinion consumers form about your brand without even visiting your website or your app.


In other words, conversation comes before conversion.

Just as the exact rules of SEO have to be rewritten every few months to account for algorithmic changes, GenAI technology will continue to change. But SEO experts have established some foundational principles over the years, and we need to do the same for AI.

Here is what we’ve learned from our own explorations and consultations with industry experts.

AI prompts are highly personal and less generic than search keywords

For decades, we’ve been building SEO tools and strategies around identifying common keywords and optimizing content to match. Users may misspell words or use slightly different phrasing, but there’s a reasonable degree of convergence around keywords like “best skincare routine.”

AI prompts tend to be much more specific. Instead of a couple of skincare keywords, a user will often provide their age and details about other products they have tried and what has and hasn’t worked for them. Rather than asking for links, they ask for detailed recommendations and a plan of action.

If you can get access to sample prompts, they can be invaluable for market research. On the other hand, it’s unlikely that thousands of people will enter the exact same prompt with the exact same details. Rather than thinking in terms of search query keywords, we need to identify common themes for prompts. In the example shown below, we’re exploring answers to questions about vacuum cleaner models, their positive and negative sentiment, and specific product attributes different brands win on.

Early theories of AI optimization

For guidance on how optimizing for GenAI is different, allow me to share the insights from experts who participated in a recent Similarweb Search Summit in London: Kevin Indig, who has been providing regular updates on the impact of AI on search through his Growth Memo newsletter and Aleyda Solís, founder of SEO consultancy Orainti, who provided an AI search optimization checklist. Here is a mashup of their recommendations:

  • Discover the right social and discussion platforms for the focus where your brand needs to win influence, prioritizing those most frequently referenced in ChatGPT answers and Google search results for key topics.
  • Simplify and structure your branded content to make it easily digestible by both people and machines. For better placement in AI summaries, Solis recommends “chunking” content into focused semantic units that can stand on their own, independent of a larger document.
  • Aim for recognition as a trusted, clearly differentiated brand. Cultivate proof points (success stories, benchmarks, certifications), experts advocates, validation by partners, analysts, reviews and press, and consistent visibility everywhere that potential customers are forming opinions and making decisions.
  • Monitor your brand visibility, sentiment, referrals from AI to identify opportunities to improve mentions that matter versus competitors. 

Example: Winning in skin care


An example of a brand with a winning share of AI referral traffic is The Ordinary in skin care. Based on U.S. web traffic, March to August 2025, theordinary.com captured a 57.56% share versus several close competitors.

An analysis of typical prompts related to this traffic shows that consumers are often either asking for the brand by name or asking questions related to the characteristics of its best known products (like “Can I use Niacinamide 10% + Zinc 1% serum with vitamin C products?”). Likely that’s because The Ordinary includes specific ingredients in their product names, where competing brands like Cerave are more likely to use terms like “foaming cleanser.”

As a result, The Ordinary has gotten out the message that these are desirable skincare ingredients, and consumers are asking detailed questions about them.

ChatGPT has gotten the message not only from the brand website but from external news and review sources. So has Google search, which includes an AI Overview summary citing The Ordinary’s content and places theordinary.com at the top of its search engine results, followed by links to a Healthline article and forum posts on Quora and Reddit.

The lesson: Paying attention to what works in GenAI visibility and how that is different from SEO is important. At the same time, improving your content and your external mentions to boost your GenAI standing is also likely to boost your search ranking – particularly as GenAI features are more tightly coupled with search.

Yes, it’s true we’re very early in the process of understanding how to optimize for GenAI. No, it’s not too early to get started.

Don’t wait.
The Rise of Agentic AI: How MetadataONE Is Transforming the Entire GTM Workflow

The Rise of Agentic AI: How MetadataONE Is Transforming the Entire GTM Workflow

marketing 19 Nov 2025

Why is now the moment for agentic AI in business and marketing?

 
Marketing tech stacks are more complex and fragmented than ever, with each paid platform running its own algorithms, bidding systems, and optimization rules. Agentic AI is emerging at the perfect moment because it can absorb the execution-heavy work, like continuous experimentation, so that marketers can finally refocus on higher-value priorities like strategy, creative direction, and understanding the customer.
 

What exactly makes MetadataONE an “agentic” GTM platform—not just another AI automation layer?

 
MetadataONE’s agents operate continuously and autonomously -  they don’t wait for step-by-step instructions from users. Instead, they run ongoing experiments, optimize for the outcome defined by the human, make real-time decisions, collaborate across channels, and learn and improve as they go. Thus, going far beyond what a traditional AI “automation layer” can do.
 

MetadataONE has dozens of agents that works together to analyze, build, create, deploy, and optimize marketing campaigns. 

 
MetadataONE’s agents work together to drive end-to-end campaign performance. A group of Analyst Agents helps identify what’s working and what’s not, evaluates winning formulas and competitive strategies, interprets data, and surfaces actionable insights for marketing teams.  Marketers can build new campaigns with agents such as Audience Builder that help build the components for new campaigns and assign a budget alongside the Creative Agent that can actually take your brand kit to generate new advertisements and copy.  The Bid agent optimizes media buying 24/7, adjusting bids in real time to maximize marketing spend. Together, another group of Agents tests and optimizes campaigns to improve autonomously without constant human intervention or oversight.
 

Different paid platforms have different audiences, data structures, and bidding systems. Can MetadataONE ensure campaigns perform optimally across each platform (Google, Meta, LinkedIn, and Reddit)?

 
Yes, MetadataONE adapts to the unique audiences, data structures, and bidding systems of each platform, whether someone’s scrolling LinkedIn during the workday or catching Facebook on the weekend. Its agents run continuous, platform-specific experiments to keep campaigns performing at their best, without marketers needing to manage every detail manually.
 

How does experimentation work within MetadataONE? 

 
Traditional optimization depends on humans doing the same slow cycle: launch a few ad variations, wait for statistically significant data, pull reports, manually determine what to  turn off, then try again next week. Marketers rarely have the time or resources to run real experiments at scale, so most teams are ‘optimizing’  a few ads and calling it a day.

We flip that model. Here’s how experimentation actually works inside Metadata:

  • Every campaign gets broken down into hundreds or thousands of micro-experiments. The platform automatically mixes audiences, creative, messaging, and bids into unique experiments you’d never have time to build manually.
  • Agents analyze performance continuously across channels, CRM data, and downstream pipeline impact for what’s driving opportunity creation and revenue.
  • Poor performers are shut off instantly and budgets are allocated to what works. No waiting for your next ‘optimization day.’ The system reallocates spending in real time.
  • Every insight loops back into every future campaign.  Humans optimize on what happened last week. Metadata optimizes on everything that’s ever worked for you.

How / Why does it outperform traditional human-led optimization?
 
Humans can’t run 500+ experiments at once or analyze CRM-to-ad-channel data 24/7. And humans definitely can’t react to performance changes in real time. MetadataONE does all of that automatically. Marketers get what they actually want: faster learning, dramatically better performance, and zero time spent babysitting campaigns.

And that’s the whole point—experimentation at a scale that’s normally humanly impossible.

As AI generates more automated activity, marketers risk chasing the wrong signals. How does MetadataONE ensure teams focus on high-value signals that impact revenue?

AI is generating a lot of noise from automated clicks, form fills, and surface-level engagement that look like progress but don’t translate to revenue. Most platforms still optimize to whatever metric is easiest to hit, like impressions or CPL, which is why marketing teams end up chasing the wrong signals that don’t result in revenue. 


MetadataONE takes the opposite approach by optimizing CRM and pipeline data from the start. It looks at real outcomes—opportunities, pipeline, revenue—and shuts down experiments that aren’t contributing and allocated budget to the experiments that are. Its agents analyze the full buyer journey across paid, website, and sales touchpoints, filtering out bot-like activity and identifying the behaviors that actually correlate with closed-won deals. Every experiment is then ranked by revenue impact, giving marketers a clear view of what’s truly working. And because MetadataONE unifies sales and marketing data into one source of truth, the platform removes the guesswork (and the arguments) around lead quality. The result: teams stop optimizing for activity and start optimizing for what actually moves deals.
How Freestar and Audigent are Powering Future-Proof Publisher Demand

How Freestar and Audigent are Powering Future-Proof Publisher Demand

marketing 18 Nov 2025

1. What prompted your team to explore curation and evolve your approach to data management in the first place?

Before joining Freestar, I spent nearly a decade on the SSP side at Magnite, working closely with the demand facilitation team to connect publisher supply with buyer demand and layer decisioning directly on the sell side. Back then, “curation” wasn’t widely discussed, but it was already clear how powerful it could be when supply partners intelligently packaged inventory based on quality, audience, and performance.

When I joined Freestar, I wanted to bring that same philosophy to our publishers. We started by analyzing which curated deals Freestar was included in and, more importantly, which signals - contextual, engagement, and audience - were consistently driving stronger results. Working closely with our demand and SSP partners, we found that curated deals delivered 2X+ higher CPMs than open auction traffic. Buyers were willing to pay more when inventory was clearly signaled and structured in a way that reflected its quality and performance potential.

As Andrew Casale, CEO of Index Exchange, has said, “Sell-side decisioning is about giving publishers control to decide which path and which buyer is best for each impression — not leaving that choice entirely to the buy side.” That philosophy aligns perfectly with Freestar’s approach. Curation allows us to embed that control and intelligence into how inventory is surfaced, ensuring it’s properly valued in a more data-driven, privacy-conscious ecosystem.

Today, more than 30% of Freestar’s supply is connected to curated deals, delivering higher CPMs, improved transparency, and stronger, more direct relationships with demand partners. At the end of the day, our job is simple: to ensure every impression is properly signaled, packaged, and positioned to maximize publisher yield. Curation has become one of the most effective levers to make that happen.


2. The case study highlights a shift from DMPs as cost centers to revenue drivers. How do you see the role of the DMP evolving?


Historically, DMPs were expensive, and only publishers with large, dedicated sales teams could easily recoup the investment. They were powerful tools, but often inaccessible to most publishers who didn’t have the scale or resources to activate their data directly with buyers.

That dynamic has changed. Through our partnership with Audigent, the DMP has evolved from a passive data repository into an active revenue amplifier and strategic intelligence layer. Together, we use Audigent’s curation-led DMP to better understand and model Freestar’s audience signals, and we lean on their deep demand-side expertise to help sell the value of those audiences and optimize toward buyer outcomes.

But the benefits extend well beyond monetization. Freestar’s Audience Development team also uses the Audigent DMP to provide our publishers with actionable insights into their users and content performance, helping them better understand who their audiences are, how they engage, and what topics or formats drive the most value. Those insights feed directly into editorial, content, and traffic strategies, closing the loop between audience growth and revenue optimization.

In the past, buyers relied heavily on their own data and third-party segments, leaving publishers in the dark about what was being layered onto their inventory. Today, the pendulum has swung back and publishers now have deeper, more accurate insight into their audiences than anyone else, far surpassing the commoditized third-party data sets that often lack precision and reliability. With the right technology and the right partnerships, they can intelligently curate and package those audiences to meet advertiser goals directly.

For Freestar, this collaboration has been transformative. By combining our network’s first-party insights, Audigent’s deal-activation capabilities, and our Audience Development team’s analytics expertise, we’re helping publishers not only drive higher yield, but also build stronger, data-informed relationships with their readers. The modern DMP isn’t just about data storage; it’s about collaboration, intelligence, and creating the cleanest, most valuable path between audience understanding and buyer demand.
 

3. What made Audigent’s technology, particularly its curation-led DMP and Hadron ID, stand out as the right fit for Freestar’s ecosystem?

Audigent stood out because they didn’t just offer a DMP, they reimagined what a DMP could be in a post-cookie, privacy-first world. Their curation-led approach, powered by the Hadron ID, aligns perfectly with Freestar’s mission to deliver quality, transparency, and efficiency across the supply path.

As Drew Stein, CEO of Audigent, explained, “With third-party cookies on the road to nowhere, we built a framework that takes different kinds of identifiers — audience-based, contextual, deterministic, and probabilistic — and creates an encrypted, encoded, and compressed shorthand.” That approach deeply resonated with us, because it mirrored the privacy-conscious, data-intelligent infrastructure we’ve built within Freestar.

What truly made this partnership work is Audigent’s dual strength: deep expertise in audience data and strong buyer-side relationships. They understand how to enrich and model publisher data while also knowing what drives performance and ROI for advertisers. As our joint announcement noted, “Publishers have incredible data at their fingertips, but it’s often difficult for them to package it in a way advertisers can utilize. When publisher partners like Freestar integrate with innovative technology providers like Audigent, it unlocks new opportunities for nearly everyone in the ecosystem.”
 
That’s exactly what we’ve seen. The partnership allows us to scale our audience data strategy across more than 500 publishers, making their inventory more discoverable and valuable, all without additional lift on their end. The combination of Audigent’s curation architecture with Freestar’s publisher-first wrapper creates buyer-ready, privacy-safe packages that amplify yield and drive better outcomes across the open internet.


4. How did you ensure the solution worked across Freestar’s diverse publisher portfolio? What results have been most exciting?

One of Freestar’s greatest strengths is the diversity of our publisher network, from hyper-niche communities to major media brands. The beauty of our partnership with Audigent is that it scales effortlessly across that spectrum. Every publisher has an audience, and through this collaboration, we’re helping them unlock the full value of that audience in a seamless, scalable way.

By integrating Audigent’s DMP and curation technology directly into Freestar’s header infrastructure, we can activate data and deliver curated deal access across all publishers, with no additional lift required on their end. It’s all about signal integrity: ensuring buyers consistently receive high-quality, structured audience and contextual signals, regardless of the publisher’s size or technical maturity.

The results have been consistent and meaningful. Audigent’s framework has driven incremental revenue and higher RPMs across the board, allowing every publisher, large or small, to benefit from sophisticated, data-enhanced monetization strategies. This collaboration underscores a simple truth: when signaling is strong and partnerships are aligned, every publisher can compete – and win – in a data-driven marketplace.


5. How do you see curation, data collaboration, and identity shaping the open internet in 2026 and beyond?

The next chapter of the open internet will be driven by collaboration and quality. As curation, data collaboration, and identity converge, the leaders will be those who can connect quality inventory, trusted data, and transparent activation into cohesive, outcome-based buying experiences.

We see a future where publishers, not platforms, define audience value. Curation and interoperable IDs like Hadron make publisher data portable, measurable, and tradeable in real time, allowing them to participate more directly in how audiences are valued and transacted. For Freestar, that means continuing to invest in partnerships that reinforce trust, transparency, and sustainability, ensuring every dollar spent on the open web delivers performance for advertisers and long-term value for publishers.

Looking ahead, we’re also preparing our publishers for the next evolution: agentic buying. As AI-driven agents like AdCP begin to make autonomous buying and curation decisions, our focus is on ensuring publishers are well-positioned to capture spend as these systems seek out the most transparent, signal-rich, and high-quality inventory paths.

Ultimately, this is a natural extension of Freestar’s core mission: to keep publishers ahead of the curve by building the technology, intelligence, and partnerships that make the open internet work better for everyone.
BDR-as-a-Service: Driving Global B2B Sales Success

BDR-as-a-Service: Driving Global B2B Sales Success

marketing 13 Nov 2025

1. What are the challenges that companies face in B2B sales today?
 
Today, sales teams face a market that is more complex and competitive than ever before, with longer sales cycles and higher customer scrutiny. In recent years, buyers have moved most of their research activity online and prefer a less hands-on sales experience. They have access to vast amounts of information online, enabling them to research and evaluate vendors independently before ever engaging with a sales representative. This creates longer sales cycles, with more stakeholders involved in each decision and a greater demand for personalized, data-driven engagement. 

Traditional sales tactics are no longer sufficient as buyers expect tailored experiences that address their unique business needs and challenges, rather than cold outreach from sellers. As a result, companies must balance the need for scale with the pressure to deliver relevant, highly contextual interactions at every stage of the buyer journey.

 Sales professionals need timely, accurate insights into buyer intent, but often lack the tools to unify this data in a way that drives actionable strategies. Combined with increased competition, budget scrutiny, and the demand for measurable ROI, these challenges make it critical for businesses to adopt advanced marketing and sales solutions that can deliver clarity, alignment, and results in an increasingly dynamic marketplace.

2. What role do BDRs play in business sales and marketing?
 
Business Development Representatives (BDRs) play an important role, serving as a link between marketing-driven demand generation and the sales team’s more hands-on engagement. Their primary responsibility is to understand prospect needs and use cases, qualify leads, and ensure that only the most relevant opportunities are passed along to sales. In an environment where buyers often complete much of their research independently, BDRs also provide the human touch that can uncover hidden buyer requirements, build trust, and align solutions with business challenges. Ideally, BDRs help accelerate the sales cycle and maximize the value of marketing investments by combining structured outreach with active listening and personalization.

 The BDR role has become particularly relevant today as the B2B buyer’s journey has shifted toward a self-service, digital-first model. While buyers expect access to resources, reviews, and product information on their own terms, they often need timely, relevant conversations with real people to validate their research and support their ultimate purchase. BDRs bridge this gap by interpreting intent signals, tailoring outreach based on a prospect’s digital behavior, and delivering insights that resonate with their unique context. In doing so, they not only move prospects more effectively into the sales pipeline but also ensure that account executives spend their time on the opportunities most likely to convert—making BDRs essential to both efficiency and growth in today’s competitive marketplace.
   

3. Can you describe what BDR-as-a-service means and how it is applied in business?

“BDR-as-a-service” is a fully managed extension of a company’s sales development function, focused on early stage business development activity. Trained BDRs expertly handle prospecting, lead qualification, and nurturing, in a flexible, scalable offering that allows a company to quickly adjust sales resources as needed. Ideally, BDR-as-a-service taps into additional capabilities such as advanced data and multilingual support to consistently build and enhance a company’s sales pipeline beyond what they could do in-house. Instead of organizations having to recruit, train, and manage their own BDR teams, BDR-as-a-service is turnkey, delivering experienced representatives who are armed with advanced buyer intelligence and best-in-class outreach strategies. 

 By leveraging BDR-as-a-service, businesses can bridge the gap between marketing and sales more effectively, ensuring that leads generated through campaigns are followed up with timely, personalized engagement. The service helps qualify prospects, nurture them through the funnel, and provide sales teams with opportunities that are both ready and relevant. Ultimately, BDR-as-a-service gives organizations a scalable, data-driven way to increase sales efficiency and drive measurable revenue impact.

4. Why would a company like Indeed.com use BDR-as-a-service?
 
Indeed operates in over 60 countries and 28 languages, connecting 610 million job seeker profiles with opportunities worldwide. In the high-potential Italian market, Indeed needed to reach more targeted accounts and support local sales representatives in generating leads and setting qualified meetings. This meant that they needed local sales expertise in the local language as well as access to data that would help identify net-new prospects as well as qualify prospects to prioritize the most relevant leads. To hire full-time staff internally would be costly and have a slow ramp time, not to mention still require third party data. Using a BDR-as-a-service model from Anteriad gave Indeed local expertise, a faster ramp and access to data. Within Indeed’s existing book of accounts, Anteriad identified and engaged Indeed’s ideal customer profile (ICP) to secure qualified meetings, which allowed the sales team to focus on advancing opportunities and driving pipeline growth. Anteriad also helped expand their target account list and enriched it with ICP contacts so that all BDRs had a larger universe for targeting.

5. What are some complexities or challenges that companies deal with when they sell to prospects in a variety of countries and languages?

The B2B sales process may start online, but ultimately, stakeholders want to know that the company they choose to partner with understands their needs and the local market, and can offer service and support on demand. If the sales process is not in the local language, or if marketing and sales does not provide relevant information about the market, it can be difficult to close leads. Simply hiring local teams is one option, but it can be very costly for a company that operates in many countries, especially when there is fluctuation or volatility in sales volume. Companies need flexibility to have resources that align to the demand they have in different regions without having to bear the cost and overhead of having FTEs in each location. 

6. How can BDR-as-a-Service help with those challenges?

BDR-as-a-service provides the perfect combination of relevant expertise with flexibility. Companies can get the local language and business understanding that they need to interact with leads without the overhead of investing in their own regional offices. Ideally, BDR-as-a-service delivers resources that can be dialed up or down depending on then needs of the client organization. For example, many businesses are seasonal, with demand coming stronger in certain parts of the year, or after certain events. Having the ability to capture that demand during busy times without having to pay extra during slower times is another benefit of BDR-as-a-services. Additionally, companies like Anteriad that offer BDR-as-a-service can tap into rich market and customer data and have highly trained professionals that are ready to deliver value very quickly. This leads to more qualified leads and ultimately more sales. 

7. What is a "warm handover" and why is it effective?

Too often, BDRs identify a lead and have a good interaction, only to hand the lead over to a sales team who isn’t able to convert the lead. This is an unintentional byproduct of miscommunication or lack of coordination between BDR-as-a-service offerings with their clients’ sales teams. The Warm Handover™ is a live, three-way intro between prospect, BDR, and the sales team designed to build pipeline, not just stack up leads. The Warm Handover holds the BDR-as-a-service team accountable, BANT criteria are confirmed on the spot, so sales reps only talk to qualified buyers. With years of expertise in regions with many different languages and cultures, Anteriad has perfected the lead handoff at a global scale to ensure that client sales teams and prospects are comfortable and the sales process is not interrupted. 

8. What should companies do when evaluating sales lead partners to get the right match for their needs? 
 
Finding the best partner for BDR-as-a-service is about finding the right combination of elements that matter most to that specific company. Some companies only need a small team in a specific location, while others may want to scale across many countries, requiring global scale. Some companies need technically savvy BDRs while others are focused on verticals such as manufacturing or healthcare. 

However, there are universal factors that all companies should have high standards for. Those factors include flexibility and seasonality, access to data and analytics to identify net-new prospects and qualify and prioritize prospects, and a process such as Anteriad’s Warm Handover that deliver leads in a way that is most likely to drive pipeline. All of these different elements must also be priced in a way that makes sense compared to investing in a full time internal resource, not just in the short term, but into the future.
Weathering the Drought: Marketing Strategies to Survive a Dry Spell in Business

Weathering the Drought: Marketing Strategies to Survive a Dry Spell in Business

marketing 13 Nov 2025

Every CEO knows the sinking feeling: phones go quiet, referrals dry up, and deals that seemed certain are suddenly “pushed to next quarter.” It’s like standing in a field under cloudless skies, watching the ground crack.

Business droughts are inevitable. The real test of leadership is what you do while you wait for rain.

This article explores how CEOs and marketing leaders can apply a farmer’s wisdom, conserving resources, deepening roots, innovating with new tools, and preparing for growth, to thrive when the pipeline slows.

The Tale of Two CEOs

CEO One: The Panic Response


When the pipeline slowed, John panicked. He slashed the marketing budget, paused campaigns, and pushed sales harder. His logic: conserve cash now, rebuild later.

But when the market shifted, his firm was invisible. No thought leadership, no visibility, no conversations. Competitors had claimed the spotlight. By the time rain came, John’s fields were barren.

CEO Two: The Resilient Response


Mary faced the same pressures. Every dollar mattered. But instead of shutting things down, she refined her strategy:

  • Cut low-yield spend (trade shows, vanity blogs).
  • Doubled down on client and partner relationships.
  • Invested in precision: account-based marketing and AI tools.
  • Protected her firm’s visibility with consistent thought leadership.

When conditions improved, Mary’s firm was already top-of-mind. Growth came faster because she had kept the soil fertile.

The CEO’s Drought Playbook

Farmers don’t just hope for rain. They adapt with deliberate, disciplined strategies. Mid-market CEOs and marketing leaders can do the same.

Here’s a practical playbook:

1. Conserve Without Starving

Farming parallel: Focus water on the crops most likely to survive.

Marketing strategy:

  • Audit spend — cut what doesn’t deliver measurable pipeline results.
  • Drop vanity metrics — measure success by proposals, meetings, and influenced revenue.
  • Protect proven channels — don’t sacrifice what consistently generates quality leads.

Practical move: Pause low-value activities like generic newsletters. Keep investing in high-ROI tactics like LinkedIn ads or targeted campaigns.

2. Deepen Your Roots

Farming parallel: Plants grow deeper roots to access reserves.

Marketing strategy:

  • Reignite dormant relationships with tailored, insight-driven outreach.
  • Create client-only value — private webinars, special insights, or roundtables.
  • Empower employees as ambassadors on LinkedIn.

Practical move: Have every partner reach out to five past clients this quarter with a relevant point of view. That’s 25–50 quality conversations.

3. Innovate Your Irrigation

Farming parallel: New irrigation methods keep crops alive in drought.

Marketing strategy:

  • Pilot AI tools for research, summaries, and first drafts, freeing teams to focus on creativity.
  • Launch account-based marketing (ABM) focused on top 25 dream accounts.
  • Tap fractional expertise (like a fractional CMO) to maximize budget efficiency.

Practical move: Run a 90-day ABM sprint with targeted ads, executive outreach, and tailored content.

4. Lead With Visibility

Farming parallel: Farmers walk the fields daily — steady and visible.

Marketing strategy:

  • Publish at least one strong thought leadership piece per quarter.
  • Stay active on LinkedIn with authentic, CEO-authored posts.
  • Show optimism — steadiness reassures both employees and the market.

Practical move: Commit to one CEO-authored post per month. Share a client story, lesson learned, or leadership insight.

5. Prepare the Soil for Rain

Farming parallel: Farmers fertilize and till before the storm clouds gather.

Marketing strategy:

  • Build case studies now, not later.
  • Refresh your website so it reflects who you are today.
  • Invest in training to sharpen business development skills.

Practical move: Task your team (or a fractional partner) with developing three new client case studies during the downturn.

Why This Matters Now

Marketing leaders today face intense pressure with tighter budgets, longer sales cycles, and leadership teams demanding ROI proof. In that environment, panic responses only accelerate decline. Resilient strategies, by contrast, not only preserve visibility but also position firms to capture growth the moment conditions improve.

The Payoff

Weather can’t be controlled, but preparation can. By thinking like a farmer, CEOs resist panic and instead:

  • Protect what works.
  • Deepen relationships.
  • Innovate with AI and fractional expertise.
  • Stay visible when competitors go quiet.
  • Prepare for growth before it arrives.

 

And when the skies open, as they always do, your firm won’t just survive the drought. It will already be thriving, ready to capture the rain.

Nift CRO Saket Mehta on redefining commerce media through AI-powered gifting, customer loyalty, and experience-first monetization.

Nift CRO Saket Mehta on redefining commerce media through AI-powered gifting, customer loyalty, and experience-first monetization.

marketing 12 Nov 2025

1. What attracted you to Nift at this stage in your career and what excites you most about joining as the company’s first Chief Revenue Officer?

Over my career, I’ve worked on all sides of the advertising equation and at companies at every stage of growth, from early stage to IPO to acquisition to Fortune 500. I was on the buy side at TubeMogul/Adobe, the sell side at Chartboost, and the publisher side at Gopuff and Block, where my focus was building and leading revenue and partnership teams. During my time at Block, Nift was a partner of ours for three years, so I’ve seen firsthand how the model drives strong revenue while prioritizing the customer experience. I was also able to get to know Elery Pfeffer, Nift’s founder and CEO, very well while working with him as a client, and I’m thrilled to join Nift now because we share a clear view of both the market opportunity in front of us and the best way to accelerate Nift’s growth.

The timing is also perfect for me to step into the CRO role because commerce media is at an inflection point. The primary challenge most revenue owners face today is monetizing CMN inventory while still offering personalized customer experiences. Brands and commerce platforms are both rethinking how to connect with consumers in ways that feel more contextually relevant and native. Nift is addressing this challenge by prioritizing the customer experience while unlocking revenue. The company is positioned to see explosive growth by solving commerce platforms’ ad challenges, and I’m excited to help achieve that.

2. In your view, how does Nift’s model differ from the retail media playbook and why do you see it as especially well-suited for fintech and other consumer-facing platforms?

Our two-sided ad marketplace, which connects commerce platforms to advertisers and brands to new customers, solves the problem of intrusive ads for consumers, platforms and brands alike.

Consumers are annoyed by traditional retail media formats like sponsored search, banner ads and sponsored product ads because they interrupt the digital experience. Commerce platforms want monetization opportunities that enhance their customer experience. And brands are looking for cost-efficient ways to reach and convert new customers.

Nift addresses the pain points of all three groups by creating positive customer moments through relevant gifting. Commerce platforms partner with us to unlock passive revenue by showing appreciation to their customers and DTC, midmarket and enterprise brands and subscription companies join our platform to efficiently lower their CACs.

Also, Nift works across all verticals, including fitness, travel, utilities and others, not just retail. And because it enables consumer-facing platforms to generate revenue without compromising the experience, it’s a particularly good fit for fintech companies like Block, Klarna and Zip, where trust and the customer experience are at the heart of the business model.

3. How do you see collaborations such as the one with Klarna shaping the broader industry’s approach to integrating ad inventory into customer experiences?

Our partnership with Klarna serves as proof of concept on multiple levels. It shows that gifting drives customer loyalty for our partners that operate consumer-facing platforms as well as brand engagement. It’s also a great example of how major fintech players are moving away from interruptive ads and toward experience-first models. In addition, it provides a framework other consumer platforms can replicate to integrate advertising in a way that’s authentic to their brand. And finally, it demonstrates how the right advertising approach can strengthen rather than strain customer relationships.

4. You’ve led advertising partnerships at companies ranging from startups to IPOs. What lessons from your time at Block, Gopuff and TubeMogul (which was acquired by Adobe) will you bring to Nift as it scales its revenue and partnerships?

The biggest lesson I’ve learned is that you always have to start by understanding the customer’s problem and focus on solving that. I’ve also learned how valuable it is to blend technology and sales in the right way to move faster. Developing real human relationships and knowing when teams need to rely on human expertise instead of digital tools are key, too.

I’ve also learned the importance of building a strong team and a great work culture. As a leader, I aim for a high “do-say ratio,” meaning people keep their word when they say they’ll do something. Experience has also taught me how valuable it is to hire adaptable team players who can move fast and learn quickly. People with those qualities are crucial to the growth of any business.

5. Can you share how AI is being applied to personalize experiences and generate incremental revenue for partners?

Nifts are thank-you gifts introducing customers to new brands and products that are relevant to them based on their history and interests. We use AI to align brand gift offers with each recipient’s preferences and behavior. Matching a customer with offers personally tailored to them drives higher engagement, and our brand partners are seeing conversion rates of up to 40%, versus 1%–3% for traditional digital ads.

We also use machine learning to identify the best moments for our partners to present a gift. Nifts can be delivered at nearly 20 different customer moments, including post-purchase, not just at checkout. For example, a partner might present a Nift to thank a customer for downloading an app, making an on-time payment or leaving a review. Partners can even offer a Nift to acknowledge a customer’s birthday or anniversary. The technology helps identify the best time and context to present the offer. Our AI also enables seamless integration into customer journeys. Nifts can be integrated into email, SMS or in-app or in-store experiences.

6. What do you see as the biggest opportunities and challenges for commerce media over the next 2–3 years and how does Nift plan to stay ahead of the curve?

Commerce media is quickly expanding beyond retail into other verticals, like fintech, travel, lifestyle and gaming, so there’s a big opportunity for us over the next few years as the market broadens. We’re seeing a shift toward advertising that enhances rather than interrupts the customer journey and an increased focus on performance, with companies looking to drive measurable, attributable revenue.

As more players enter the commerce media space, differentiation will become harder. But the biggest challenge will still be balancing integrations that feel fully native with authentic customer experiences that don’t feel intrusive. Think about a financial services company that presents a non-endemic banner or video ad on its platform. The ad disrupts the experience and annoys the customer. The company can avoid that, and add value to the experience instead, by presenting an offer that acknowledges and rewards the customer for a specific action, like making a second on-time payment or opening a new account.

Nift is focused on staying ahead by being a first mover into new categories, like we are in fintech, where our recent partner launches include Klarna and Zip. We also let platforms connect with customers at multiple touchpoints, not just during the transaction, so offers are well-timed and delivered through the right channel for each customer. And we’ll continue to lead with proof of results, focusing on the outcomes while ensuring the consumer experience is repeatable.

7. How do you see Nift’s growth impacting consumer loyalty and brand engagement in the long run and what role do partnerships play in scaling that impact?

Nift is building the foundation to become a primary channel for brand discovery by 2026, giving platforms a way to deliver relevant, well-timed offers to customers. Our growing partner ecosystem will be key to scaling that impact, especially as we expand internationally. Strategic partnerships with platforms that are leaders in their industry drive credibility for our solution, expand our distribution and create network effects where every new platform and brand increases the value for all participants.

Lori Rosen on PR’s Evolution in the Digital Era

Lori Rosen on PR’s Evolution in the Digital Era

marketing 12 Nov 2025

1. Having represented media brands and publishers from the magazine era to marketing agencies and content creators today, how has the evolution of the media space shaped the way you approach PR?

We have always followed a top-down public relations strategy, with a focus on national media outlets in television, radio, and print, as well as industry outlets in the B2B space. But as the media landscape expanded and fragmented across digital channels, new opportunities for coverage emerged. This shift encouraged a “more is more” approach, as national media hits began to have shorter life spans. At the same time, coverage—whether national or regional—now lives on beyond its initial run, shared and amplified across digital channels, newsletters, and social media, giving a lasting presence and enduring shelf life. The evolution continues to take shape. Podcasts and Substack writers have expanded the media universe again, and our strategy has adapted to actively target these emerging platforms.

2. For media brands, publishers, content creators and marketing agencies, what are the key ingredients of a successful PR strategy?
First and foremost, companies in the media and marketing space must execute a solid thought leadership campaign. Be willing to comment on timely topics—and say something different from everybody else. That’s how you stand out, and how you demonstrate true thought leadership. After all, what’s the point in commenting if you’re simply saying what everybody else is saying? Media industry leaders must be ready and poised to create their own content via newsletters, bylined articles and blog posts, as well as manage a robust LinkedIn presence. Staying front and center is key, and being viewed as a thought leader in your field of expertise will keep you ahead of the competition. Further, consistency is critical; a one-off effort isn’t going to achieve the same impact as a sustained, long-term campaign.

Beyond that, availability and responsiveness are also critical. In a marketing and media landscape where everything moves so quickly—major announcements, brand controversies and industry shake-ups included—you want to earn the reputation with reporters and producers as a trusted source who can reliably deliver quick, insightful commentary on a tight deadline. A strong PR partner will pave the way to building that rapport with key media contacts.


3. Over the years, the lines between PR, marketing, and digital have blurred. How has this convergence reshaped client expectations and the role of PR firms?

The lines between PR, marketing, and digital have always overlapped, but today the role of PR agencies has clearly expanded. Agencies are now expected to manage comprehensive content strategies as an integral part of campaigns—developing website copy, articles, blog posts, email newsletters, and even coordinating events. Increasingly, they’re also tasked with running social media campaigns. While this may appear to be a natural extension of PR, in practice social media campaigns require a different set of skills, with greater emphasis on design, agility, timeliness and cultural sensibility. Throughout the years, I’ve always found the evolution of our industry exciting and invigorating, and today is no different.


4. You’ve compared the rise of AI to the early days of Google. Can you expand on that comparison?

In the early years of Google, it became evident that articles and backlinks from authoritative domains significantly influenced search rankings, often determining whether a brand appeared on the first page of results. As a result, media coverage became an essential component of SEO strategies. This dynamic persists in the current era of artificial intelligence. Brands, marketers and PR practitioners are learning to navigate and leverage AI tools in a way that benefits their businesses. Like we’ve seen with SEO, positive press drives website visits and overall brand presence. However, negative press can also wreak havoc on search results, living in full view online for years. Media coverage continues to play a central role in shaping how companies surface in searches, underscoring the enduring importance of digital strategy. We, as PR professionals, must be nimble and adapt to meet our clients' needs in a world that is continually advancing in technology.


5. How should agencies balance the use of data-driven tools with the need for creativity, relationships, and storytelling?

Let’s start with storytelling. That is the most effective tool in the arsenal. Creativity and relationships are a close second, and the data-driven tools should be used for polish and efficiency. There are no shortcuts; you cannot circumvent creativity. However, it is important to embrace new technology and leverage it accordingly. Effective ways to use AI include:

• Embrace it like a highly customizable tool, or even a co-worker—not a crutch.
• Bounce ideas off ChatGPT; ask questions, ask follow-up questions.
• Give feedback so it knows why you chose the response you did over the other ones.
• Use it for ideation, format suggestions and design concepts, but not as a substitute for judgment and critical thinking.
• Aim to think of yourself as an artist and a scientist; if you struggle to find that balance, collaborate with a coworker whose strengths complement your own.


6. Many marketing and technology brands are competing for visibility and credibility. What advice would you give them to stand out in today’s marketplace?

Where do I begin? First and foremost, standing out requires a commitment to a long-term plan. Understand that visibility is not achieved through a single quick fix or isolated success. It is not just the iconic New York Times profile, the AP feature, the high-profile podcast appearance, or the viral social media post. Nor is it only the bylined article in The Wall Street Journal or the CNBC appearance. True impact comes from the cumulative effect of all these efforts. Consistency is essential. Much like cultivating a thriving plant, a PR campaign must be nurtured over time to remain vibrant and top of mind.

If I were advising the OG technology leaders (aka Mark, Elon, Jeff), I would advise them to tone down the decadence and up the empathy factor. Leverage your resources to organize worldwide volunteer efforts for good or build housing for homeless people in distressed areas. Put your talent and resources to good work, and the public would be happy for you to boast about it. Think of other iconic leaders that we admire, such as Lady Diana, who went into minefields; Warren Buffett, who committed to giving most of his money away; and Oprah, who literally built schools for girls in Africa.

More realistically, for non-household name technology and marketing brand leaders, it is important to take a stand and be authentic. People crave authenticity. We would also recommend creating and owning an event that showcases your company’s unique strengths on a broader stage and exists separately from the day-to-day business. Another powerful tactic is to revive the pre-dot-com tradition of meetups. They foster community, build brand equity, and deliver real value. Plus, they are fun.

MADTECH.AI's AI-Powered Marketing Intelligence Helps Brands Turn Fragmented Data into Competitive Advantage

MADTECH.AI's AI-Powered Marketing Intelligence Helps Brands Turn Fragmented Data into Competitive Advantage

marketing 12 Nov 2025

Marketers today are surrounded by siloed, disconnected, and unusable data and struggle to convert it into smart decisions fast enough. We built MADTECH.AI to bridge that gap and make AI-powered marketing decision intelligence (MDI) usable for all. It is increasingly clear that “Speed to Value” is becoming essential because leadership demands measurable results with a minimum of waste. Our mission is to simplify marketing analytics complexity so marketers can act with confidence and make a positive impact.

 

Your platform is “purpose-built by organization type and user role.” Can you explain how this approach simplifies complexity for both B2C and B2B marketers?

A retail marketer, a B2B strategist, and a CMO all need vastly different signals. Our platform is designed to deliver tailored insights by role and organization type, so users see only what matters most to them. This eliminates noise and reduces the time spent digging through irrelevant data. The result is faster, more accurate decision-making across the board.

 

You talk about making insights “accessible to all.” Why is democratizing data and analytics so important for the industry right now?

Data silos and reliance on technical specialists often slow down smart decision-making. By democratizing access to data and insights, we empower everyone so they can use data confidently. This creates a culture of agility and alignment across the organization. In an industry moving at high speed, accessibility is the foundation for innovation and growth.

 

For emerging brands or agencies with leaner resources, how does the platform help level the playing field?

Smaller teams often lack the budgets or talent pools of larger enterprises. We provide them with pre-built models, automated pipelines, and AI-driven recommendations that are ready to use. This allows lean teams to unlock enterprise-grade marketing decision intelligence without the overhead. In practice, it means they can compete on equal terms with bigger players.

 

Where do you see the biggest opportunities for innovation in MarTech + AdTech over the next five years?

The next leap is AI-based Marketing Decision Intelligence. This is deeply data-connected AI that not only reports activity and performance, but also predicts and recommends actions in real time. We’ll also see stronger convergence of MarTech and AdTech, driving unified cross-channel and cross-platform customer journeys. Privacy-first personalization will shape how brands engage with audiences. Together, these trends will redefine speed, precision, and effectiveness in marketing.

 

What advice would you give to marketing leaders who want to become more data-driven but feel overwhelmed by complexity?

Start by focusing on one or two areas where data analytics can deliver a visible impact quickly. Small wins delivered quickly build confidence and momentum for broader adoption. Choose platforms that remove complexity and make insights easy to use. Most importantly, foster a culture where sharper, smarter, faster decisions, and not just descriptive dashboards and scorecards, define being “data-driven”.

   

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