Updated 23 December, 2021.
How Predictive Intelligence Helps Connect Customers to B2B Solutions
In the past few years, coinciding with the rapid rise of artificial intelligence technology, the field of predictive intelligence has been growing quickly. Today, predictive intelligence is not just a theoretical framework — it’s a selection of well-adopted products and services that help sales and marketing teams solve real business problems and achieve better business outcomes.
What is the science of predictive intelligence exactly? How can it help your sales operations reach its business goals? And why is predictive intelligence often considered to be the most promising technology to change sales and marketing in the near future?
What Are Predictive Models Based on Artificial Intelligence?
As with any new technology, the definition of predictive intelligence varies somewhat depending on the source you’re reading. Often, the records for predictive intelligence even get bundled up together with other “predictive” terms, such as predictive analytics, predictive recommendation engines, and predictive marketing. Broadly speaking, all of them essentially describe the same concept.
Predictive intelligence takes root in behavioral science and is generally defined as the process of collective and processing behavioral data (related to users, customers, leads, or visitors) from a variety of sources to accurately foresee future actions and events.
All the data that predictive intelligence tools collect gets automatically interpreted, with the help of algorithmic models that can take into consideration millions of data points and arrive at data-backed and action-ready conclusions in mere seconds.
Note that most of the predictive intelligence models in the marketing space are limited by the hypothesis or framework that the engineers have defined, instead of having the self-learning capacity of true AI.
The essence of predictive marketing is then leveraging behavioral science, complex mathematical models, and vast amounts of data to inform marketing strategy and ultimately reach your business goals.
One of the most common user intentions that predictive analytics can foresee is churn. Armed with this insight, you can create new product marketing campaigns, reorganize your company operations (e.g. hire a customer relationship manager), and make iterative changes to your products or services.
Another example that predictive models based on artificial intelligence can solve is estimating click-through rates on advertising. Predictive intelligence is about constantly analyzing data and helping you decide on the best-performing visuals, tone of voice, and medium to use in your marketing campaigns. Finally, you have the technology to personalize your communications at scale.
How Accurate Are B2B Marketing Technology Predictions?
We now know what predictive intelligence does. But how effective are such predictions at actually moving the needle?
A Forbes Insights report surveyed 308 executives in North America working for companies with at least $20 million in revenue and found that 86% of them recorded increases in their ROI due to using predictive marketing platforms.
The efficacy of predictive intelligence is two-fold. On the one hand, it works based on raw records and data, initially removing the emotional (human) component from the equation when it comes to interpreting various events and other results.
On the other hand, predictive intelligence is able to process greater pools of data — both in terms of quantity and complexity. Such prediction analysis could never be done by a human in such a short amount of time. This ultimately leads to better ideas and improved marketing operations.
What Are the Future Predictive Intelligence Products & Services?
Many predictive intelligence tools work in the B2B market, where they can rely on a wealth of customer data from a variety of sources and use it to come up with accurate insights, score leads, and determine buyer intent.
Every year, the frameworks and models that guide predictive intelligence solutions are improving. However, the biggest improvement seen so far has been from the introduction of machine-learning technology and artificial intelligence.
This differs from what we consider “predictive intelligence” in that it improves its own predictive models in order to “learn” and reach a specified success state. This is true machine learning, not based on behavioral science hypotheses.
In order to do this, and make it work effectively, the initial machine learning platform needs to be fed vast quantities of data, events, and scenarios to guide it.
Analyzing various types of information allows machine learning to process more subtle cues from unstructured data or seemingly “disconnected” data points that a predictive analytics product created by a human might not see or account for.
The leaders in this market aren’t necessarily large, well-known companies like IBM or Salesforce. There are lots of smaller players — each one aggregating and specializing on data that services its own users. For example, when it comes to identifying anonymous buyer intent, there’s nothing more powerful than Lift AI.
Lift AI is the best-in-class anonymous buyer intent solution that can accurately pick out the most promising leads in the sea of your website visitors.
Relying on its proprietary machine-learning model trained on more than one billion data points and 14 million sales engagements, Lift AI is able to predict how likely every single visitor to your website is to buy your solution, even if they are completely anonymous (up to 98% of any average website traffic). Plus, it all happens in real-time.
Here’s how the Lift AI works to increase your website performance:
- Visitors land on your website
- Lift AI predicts their buyer intent (with 85% accuracy) by matching their displayed behavior to modelled behavior
- High-scoring visitors get connected directly to your sales team for conversion through online chat
- Medium and low-scoring visitors are assigned to a nurturing bot or a self-help guide
Lift AI has found that, on average, 9% of website traffic for any company has high buyer intent and is ready to try new tools and solutions. By connecting that 9% of high-intent traffic to your best conversion channel possible (real-time chat with a live salesperson), you can significantly increase your website’s performance. In fact, it works so well that within 90 days most companies see their chat conversions increase by two to 10 times, since BDRs are mostly talking to people who actually want to buy.
Now you can see how predictive intelligence can improve long-established sales and marketing processes in seconds. By letting machine-learning models do what they do best, you can reap the benefits of higher conversion rates.