On its own, intent data is incredibly powerful. But it becomes exponentially more so when used alongside AI and machine learning to predict behavioral trends and selling opportunities.
What is Predictive?
Leveraging vast amounts of historical data and real-time insights, 6sense employs predictive models to forecast future behaviors and purchase intentions.
Through machine learning algorithms, 6sense continuously refines its models, incorporating new data points and adjusting predictions based on evolving market dynamics. This technology enables businesses to anticipate prospects’ needs and preferences and where they are in the buying journey so marketing and sales outreach can be tailored to deliver the right message at the right time.
There are three foundations to 6sense’s predictive models:
- Fit: Know who your ideal customers are.
- Reach: Know how well you are reaching buyers.
- Intent: Know when buyers are in-market.
Predictive Analytics takes the billions of signals and matched to accounts and compares those signals to your historic data to spot the accounts that are behaving the most like past buyers. From there, you’re served up the accounts that are most likely to purchase, as well as details showing the best way to engage with them at any stage in their buying journey.
6sense customers that use predictive capabilities have seen:
- 39% more opportunities
- 13% more wins
- 45% larger deals
- 38% shorter deal cycles
Let’s look at how predictive and intent data can win at every buying stage.
Target Stage
Accounts in the Target stage are often at the very beginning of their buying journey, potentially unaware of your products, services, or even your brand.
By integrating predictive analytics with intent data, you can anticipate the needs of these accounts before they actively begin their search. This proactive approach allows you to tailor top-of-funnel content more precisely.
For example: You may not have keyword research data yet, but you can use firmographics, technographics, and historical behavioral data to predict potential pain points and interests. Create personalized sections on your website that serve up high-level content about specific pain points your products solve.
Awareness Stage
In the Awareness stage, buyers have started their research journey and may be aware of your company. They’re starting to show signs of life. In this stage, you want to start lightly targeting these accounts with some buying stage campaigns.
Analyzing intent data through predictive models enables you to determine the topics potential buyers are researching. Predictive analytics use AI-driven insights to forecast buyer behavior and identify when they are most likely to engage, allowing you to time your campaigns more effectively.
For example: Serve up targeted display ads that educate the buyer about the solutions they’re seeking. Steer them toward:
- Helpful blog posts describing common problems and solutions
- Downloadable checklists they can use to identify their needs
- Links to third-party studies and analyst reports that deliver unbiased insights
Predictive analytics also enhance website personalization by enabling smarter chatbot interactions. Based on intent signals and predictive insights, chatbots can suggest the most relevant content to visitors, aligning with their current interests and buying journey stage.
Consideration Stage
Here, accounts are homing in on specific solutions and potential vendors — including your competitors. If they’re not considering your company at this point, you are behind the curve.
Predictive Analytics not only identifies what topics and solutions these buyers are looking for, but also anticipates their next moves. This empowers marketers to create highly personalized and timely campaigns that effectively address those buyers’ anticipated concerns and interests.
For example: Provide content that focuses on ways you can solve the specific challenges the buyer has identified — and how your solution stands out among vendors. Consider using:
- Blog posts that discuss specific challenges in-depth, and detail how you can solve those issues
- Downloadable guides that compare features and pricing, especially relative to competitors they may also be researching
- Case studies, customer reviews, and testimonials that bolster your credibility and value
Decision Stage
You’re entering the late stages of the deal and a decision is coming soon. Accounts aren’t ready to negotiate a deal, but they are ready to engage with sellers directly.
(Without intent data and predictive intelligence, this is often the first time sellers become aware of an opportunity! That’s way too late.)
Now is a great time to focus on multi-threading to make sure you are engaging with as many buying team members as you can. Predictive analytics can guide your sales team on the optimal timing and messaging for outreach, ensuring that communications are timely and relevant.
For example: Armed with insights from both intent data and predictive analytics, sellers can schedule demos or meetings when intent data indicates interest levels are at their highest. Additionally, you can identify relevant members of the buying team to personalize engagement for every individual.
Purchase Stage
This is the final stage, where a buyer will select their vendor. All the chips are on the table.
Predictive analytics enhances the use of intent data by providing foresight into potential objections and concerns that may arise just before the final decision is made. This allows salespeople to prepare and alleviate those issues proactively.
For example: Pay attention to intent signals mapped to different buying team personas. This can help you understand the unique priorities of every decision-maker and anticipate potential roadblocks.
