Today’s buyers expect personalized experiences online, whether they’re looking for a pair of dressy shoes or for a SaaS technology to make their jobs easier. Companies are taking note: Those that excel at personalization generate 40% more revenue, McKinsey reports.
What’s the secret to delivering these kinds of persuasive, relevant customer experiences? Smart audience segmentation.
In theory, segmentation is very simple: You categorize prospects and customers into different lists based on their interests and known characteristics. Then you deliver sales and marketing messages that align to the interests of the people on those lists.
Leveraging artificial intelligence simplifies the complex process of generating lists and delivering perfectly timed messaging. Even so, segmentation can get tricky. Let’s take a closer look to discover why — and how to sidestep those challenges.
Generic Persona = Generic Content
Many B2B marketers don’t know enough about individual buyers to accurately place them in specific audience segments. This is because the buying journey is normally opaque, with about 70% of the journey happening through anonymous online research.
This means your revenue team doesn’t know:
- What prospects are researching
- What content they have consumed
- What information they already know
- Which company they work for
- Whether they are even truly considering a purchase
Without visibility into a buyer’s goals and intentions, it’s impossible to deliver the type of personalization that drives revenue breakthroughs. Instead, you’re forced to deliver generic content based on broadly-defined personas.
And those personas and the ensuing messages, unfortunately, are often tailored like a cheap suit: One size fits all… and it fits almost everyone poorly.
That’s not because of a lack of skill. It’s because of a lack of tools.
Fortunately, modern AI-driven tools that gather and analyze intent data enable you to spot buyers, track their interests, and deliver campaigns that are precisely calibrated to meet their needs — and turn them into customers. This completely changes the game.
Let’s see how with this example, featuring a fictional buyer named Bob.
What (Do You Know) About Bob?
So you’ve built a target account list (TAL), and among the thousands of people who fall within your TAL is a buyer named Bob. All you know about him is that he works at a relevant B2B organization.
Unfortunately, there’s a lot you don’t know, such as:
- What are Bob’s unique pain points?
- Is he in the market for a solution like yours?
- Is he even part of his organization’s buying team?
Without these answers, you have little choice but to create generic messaging that appeals to a broad persona and hope that it resonates.
The Tragedy of Generic Targeting and Content
For a moment, let’s assume Bob is a buyer. If you’re lucky, your campaign will inspire him to learn more, but if he encounters nothing but generic content, he’s much less likely to engage.
At the same time, your campaigns and ad dollars are also hitting other buyers, including Sally and Jose and Ahmed and Nushi — none of whom have any immediate interest in your offering. That’s a lot of wasted time and money to reach people who were never going to buy.
What ‘Better’ Looks Like
Now, let’s say you’ve implemented a revenue intelligence tool that uncovers robust account and buyer details. Not only do you know technographic and firmographic information about the business Bob works for, but you also know when someone in his organization is actively looking for the solution you provide.
The person searching might not even be Bob. It might be a different member of Bob’s buying team, or someone from a completely different department. The right revenue intelligence tool can help you:
- Spot when a member of an account is engaged
- Provide clues about which individual is doing research
- Show you what is being researched by engaged buying team members
- Help you identify other likely members of the buying team and capture their contact info — including Key Decisionmaker Bob.
Bingo!
Armed with robust information about the accounts and the individual buying team members in your pipeline, you now have the ability to create specific audiences, which then lend themselves to hyper-targeted and focused messaging.
Which brings us back to audience segmentation.
Traditional Segmentation vs. Dynamic Segmentation
Marketers have used conventional audience segmentation for years to improve their messaging. But dynamic segmentation elevates your capabilities by automatically assigning contacts to designated marketing lists. This eliminates the manual process of updating lists.
Manually updating lists is so time-consuming that marketing departments often only update lists every few weeks — or months. During this lag time, a customer’s needs may change. Meanwhile, your lists are stagnant. Many of your customers will have shifted, but you’ll still be firing off messages that are no longer relevant.
Dynamic segmentation will automatically move prospects and customers to different audience segments based on criteria such as:
- Buying stage
- Company annual revenue
- Sites they’ve visited
- Keywords they are researching
- Interactions with your web properties
If any attributes change, the buyer may move from one segment to another (hence the dynamic part).
With these filters set and buyers sorted into the proper audience segments, you can frame your product or solution based on their particular needs.
Dynamic segmentation is instant, because AI can spot shifts in your customer’s behavior and automatically reassign them to new campaigns. When they stop searching “how do I…” and start searching “who is the best provider for…”, you can instantly shift from sending educational content to sending highly relevant information based on the keywords he’s been researching — or an invitation to book a demo.
Automated alerts can also be deployed to your sales team so they know that it’s time to begin direct outreach.
Conclusion
With a full picture of who Bob is, his pain points, and his unique buying signals, you can easily reach out to him with valuable and impactful messaging right when he needs it. By giving him just what he’s looking for, you’ll be much more likely to land him and his company as a customer.
6sense intent and predictive data empowers revenue teams to:
- Reduce wasted time and resources
- Better allocate spend by accurately identifying where buyers are in their journey, Target accounts ready to engage, and
- Have more meaningful and relevant conversations with in-market accounts
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