Picture these two scenarios—which do you think is a better experience?
Scenario A: I go to a B2B website, and am greeted with “Hello PathFactory” along with our logo. Pretty cool they know what company I’m coming from. I navigate to content, and I’m offered up the same stale whitepaper as everyone else in my industry. Reluctantly, I click it and start reading.
Scenario B: I get home and log into Netflix, after a long day of reading thrilling whitepapers. Right away, I’m given an enticing array of shows to pick from. The newest standup comedy specials. The rest of a documentary I got halfway through last weekend. That new Ali Wong movie.
Safe to say Scenario B is going to lead to a several hours long binge, while Scenario A is going to lead to a lukewarm perusal at best.
What’s the major difference between these two scenarios? The data that powers these experiences.
While I admittedly may never be quite as thrilled by B2B content as I will by Jon Mulaney’s musings, B2B marketers still stand to learn a lot from the streaming giant about using AI to enable people to binge their content.
Most B2B marketers aren’t yet capturing the right data set to allow them to use AI to their advantage. If they could collect data beyond just their prospects’ demographics & firmographics, they could educate their prospects quicker, in a more seamless and delightful experience.
In this blog, I’ll share the types of data that power Netflix’s AI, and how B2B marketers can take a page from their playbook to move qualified leads through their funnels faster.
How Netflix is able to personalize better than almost anyone
How does Netflix consistently give such bang-on recommendations? The differentiator is in the data. Netflix’s unparalleled data set paves the way for successful micro-personalization and a consistently high share of their audience’s personal time. It collects behavioral data about what content users consume, as well as metadata about what that content is about.
Each movie or show on Netflix has rich metadata attached to it—for example, actors, directors, genre, reviews. The platform also tracks behavioral data like device type, time of day when content is accessed, and play time. This data set allows the AI-based recommendation algorithms to make the best personalized recommendations that keep users hooked.
Netflix can distinguish between somebody who watched five minutes of Stranger Things and somebody who binged the entire first season in one sitting. It can then use this consumption data, paired with metadata on what the content is about (“thriller,” “nostalgia,” “Winona Ryder,” “science fiction”) to offer recommendations based on that information.
The combination of sophisticated AI technology and proprietary data allowed Netflix to disrupt an entire industry. (Remember Blockbuster, anyone?) Data in two main forms—content metadata and content consumption data—made it possible for Netflix to engage their viewers exactly how they want to engage. That is a lesson that all B2B marketers can apply to their own strategies.
How B2B marketers can apply this formula to boost demand generation efforts
Netflix pioneered a winning formula to capture engagement:
Content metadata + content consumption data (multiplied by AI algorithms) = unparalleled engagement with content
If B2B marketers can replicate a similar model when it comes to educating their prospects, they’ll convert more leads faster, and outpace their competitors.
Think about it like this: When you get home from work, you can’t afford to spend 20 minutes surfing the television guide when you only have an hour to watch TV. You need a manageable set of hyper-relevant, curated content recommendations based on your previous viewing history that make it easy to relax in front of a good show.
B2B buyers are no different when they’re searching for the info they need to make a purchase decision. They don’t have time to hunt through your website or content repository to find the info they need. They need to be delivered a curated set of content recommendations whenever and wherever they choose to engage. This is the key to keeping them hooked and arming them with the information they need to confidently make a purchase decision.
B2B needs to start collecting the right data in order to personalize like Netflix
If B2B companies can collect similarly robust data on their buyers and their content consumption, then AI can allow them to use this data to keep them consuming content with spot-on recommendations. However, since AI is only as good as the data it’s fed, marketers need access to a whole new class of data to make this possible.
B2B marketers often rely on clicks, page views, and form fills to determine if a prospect engaged with their content. But these metrics can be misleading. They tell you whether or not an individual accessed a piece of content, but they don’t tell you if they actually spent time reading it. Bob, who spent 5 seconds on your new whitepaper, registers exactly the same as Sally who spent 8 minutes 32 seconds poring over every word. To your martech stack, both of these activities look like 1 form fill.
That blind spot is a big problem for marketers. Finding out what happened after someone clicked—whether they spent meaningful time reading or if they exited right away— is essential to understanding if the touchpoint was successful.
Engaged intent data is a new class of first-party data that looks not only at topic clusters but also at how these topics intersect with consumption data of individuals and accounts. With engaged intent data, not only can you see the specific topics a buyer is accessing you can also find out if there is a meaningful interaction with that content. This allows you to differentiate between, for example, those who accessed an asset but quickly bounced, and those who spent several minutes digesting it. This data set is what is truly needed to orchestrate the buyer’s journey at scale.
Why AI-powered personalization is becoming so important
In a world of Netflix, Uber, and Spotify, seamless on-demand experiences are becoming the norm. (Think about how patient you felt the last time you had to wait 8 whole minutes for an Uber.) Today’s consumers are used to getting what they want, when they want it.
This expectation is rapidly seeping into the B2B world, where a similar standard of experience is starting to be demanded by consumers. Many B2B brands are struggling to meet this raised bar, but the companies who are embracing this new expectation are coming out on top. Striving to give your buyers frictionless experiences using AI is exactly what you need to gain an advantage in an ever more competitive marketplace.