This year’s SiriusDecisions Summit brought together over 3,000 marketing, sales and product leaders to learn best practices for driving greater alignment and top line revenue growth. The week was a blur of workshops, private dinners and breakout sessions, but the most instructive for me was a SiriusDecisions case study, Building The (Artificially) Intelligent Revenue Engine, which examined how PureStorage made the move to using AI to understand their customers at scale.
The session was hosted by SiriusDecisions analysts Kerry Cunningham and Monica Benhnke. Across fifty minutes they walked us through their new AI Matrix for B2B Marketers, and why the enterprise cloud storage company turned to artificial intelligence to deliver a personalized experience across its digital channels.
As with many enterprise B2B companies, PureStorage has a complex portfolio of products endpoints, buyer personas and content journeys. This necessarily leads to problems such as low engagement, prolonged nurture cycles and fewer net new leads because of imprecisely marketing to segments (instead of segments-of-one) and the inability to put buyers onto the right nurture path.
PureStorage recognized that they needed to be more relevant to improve engagement, but had to grapple with the trade-off of either getting more personal (smaller segments, gather more specific insight) or getting wider results (contact more people to try and generate greater return). The answer could not resolved by their current marketing automation stack; marketing technology had helped their marketers achieve scale but its reliance on manually-built automation rules meant it was impossible to deliver a truly 1:1 experience on web and email with their current internal resource.
The company turned to SiriusDecisions and their latest matrix to help them deploy artificial intelligence and integrate it into their marketing automation stack. It’s no surprise PureStorage are now using artificial intelligence. AI takes the unstructured data generated by buyer behavior can turn it into actionable insights (such as buyer intent) and execution (such as deciding what content item is put in an email to an individual buyer). Consequently, AI is now being used by B2B organizations that want to deliver personalized B2B experiences.
SiriusDecisions advise B2B organizations that want to understand their customers at scale with AI to:
– Identify a known business goal or need for AI
– Gain a “high definition” view of the buyer universe
– Use AI to analyze and optimize the relevant buyer datapoints
– Lean on third party data until orgs have built their own first party dataset
Ultimately, PureStorage adopted an AI solution for automating content tagging, enabling personalization and web visitor profiling at scale to drive content engagement. The AI ‘reads’ web assets (content) and maps the content to the appropriate product endpoint, visitors to the website are tracked and a unique buyer profile is intent based on their content consumption behavior, this is then used by the AI for content decisioning on the website. The results included click-through rate up 158% and onsite form-fills via gated content assets up 289%. This is the power of using AI to understand customers at scale.
The key takeaway from Kerry’s presentation was the simple idea that lack of data need not hold back B2B organizations from using AI, ”Large companies come to us wanting to sort out their data before they start adopting AI for marketing. But it should be the other way around – your first use case for AI should be cleaning up your data.” This was a view echoed by Tom Libretto, CMO of Pegasystems, in another SiriusDecisions session when he discussed how the organization used AI to gain a deeper knowledge of buyer intent on over 3 million customers.
The wider learning for other B2B businesses is that if you want to understand your customers at scale and deliver a personalized experience, AI applications are rapidly superseding marketing automation to this end.