CDP Institute

EU regulations and US court rulings are loosening Google and Apple’s control over app store purchases. One beneficiary is Appcharge, which provides alternative technologies for direct-to-consumer sales by mobile game developers. They’ve grown 14x in the past twelve months and just raised a $58 million Series B, only nine months after a $26 million Series A.

Founded just last year, Evertune is one of the swarm of companies offering to help brands improve results of AI search. They just raised a $15 million Series A, bringing total funding to $19 million, and announced plans to build “the AI marketing suite of the future” to prepare companies for the day when agents make purchases on behalf of consumers. Most interesting was their explanation of how they optimize AI search: they run over 100,000 AI prompts to understand how each brand appears in AI search results.

We reported last week that IT staff are very pleased with how well they’re preparing customer data. Data consumers are less satisfied: this Ascend2 report for data governance vendor Collibra finds that 40% of data governance, risk and compliance professionals don’t trust their data and 62% say data quality is the top area needing improvement. When it comes to building AI models, data reliability is the top challenge (53%), outweighing compliance (45%) and risk (41%).

Customer engagement platform Braze avoids the CDP label but its year-old Data Platform ticks all the boxes: it ingests data, builds and stores unified customer profiles, and shares the results with other systems. They’ve just announced plans for further enhancements, such as CSV data imports for custom events, as well a Model Context Profile (MCP) server that lets user query Braze data with genAI prompts.

MCP servers are clearly a fashion must. Customer data tool vendor Aqfer just added one of their own. In their case, MCP provides AI systems with access to enterprise data that remains in cloud data stores. Aqfer’s contribution is structuring, governing and contextualizing the cloud data to serve marketing use cases.

Marketers often cite poor data quality as an obstacle to AI success, but IT and tech professionals surveyed for DataBank have a rosier view. They cited technical issues, including integration, scaling, and deployment, as the biggest obstacles to AI success, while ranking data quality and access fourth on the list. An impressive 71% said their customer data is “very well prepared” for AI use, a far higher rate than any other data type.

Are you tired yet of hearing about companies that help marketers optimize content for AI search engines? Then you might appreciate that this announcement from Siteimprove is only partially about that. They’ve just launched a posse of agents that deal with accessibility compliance, provide insights into content performance, guide content creation (and write drafts), orchestrate content workflows, and, yes, optimize content for human and AI search consumption.

The reason we’re hearing so much about optimizing for AI search is that it’s growing fast: Brightedge reports that referrals from ChatGPT grew 21% in a single month this July. Unfortunately for publishers, website visits by the ChatGPT agent doubled, meaning a growing share of queries were resolved without humans reaching publisher pages. This doesn’t bode well, although it’s hard to interpret the data because the report doesn’t show the actual number of searches.

“Hidden buyers” is a polite term for people, such as IT, finance, and legal staff, who don’t use a system but are still involved in the selection process. Business users would often offer a more colorful description when those people slow the purchase process or disagree about which vendor to select. This LinkedIn study for Edelman confirms what those business users suspect: hidden buyers care less about reliability and technical details of a system than vendor vision, insights, and attractive marketing.

Treasure Data has announced a new pricing model that removes compute costs from the equation. Fees will now be based on number of customer profiles and behavioral events such as website visits and email activities. The new approach allows companies to reduce cloud data warehouse compute costs by shifting some data and processing to the CDP while still accessing cloud data warehouse files directly when appropriate.

It won’t be long before we lose track of all the companies helping marketers to manage how their company appears in AI search results. But for now it’s still interesting enough to report that Profound, whose AI agents monitor results, generate content, and runs campaigns, has just raised a $35 million Series B. The company has reached more than 500 customers since launching less than one year ago.