It’s better to aim for 10 targets that are more likely to buy rather than 10,000 targets who aren’t ready to make a purchase. Would you agree? Gartner has made it known that predictive analytics experienced tremendous growth in the B2B world within the past few years. Why do you think this is, and how can you make the most of intent data? Learn why intent data is the missing link regarding predictive analytics.
The State of Predictive Analytics Within B2B Marketing
What do you think the state of predictive analytics is within the B2B marketing landscape? To this day, numerous B2B companies leverage predictive analytics to narrow down a list of their main prospects. From there, they often hire analytics providers to analyze past data, the history of their data, and timelines of different accounts by using various statistical techniques like data mining, machine-learning, and predictive modeling.
In addition, these analytics providers are responsible for analyzing data within the limitations of their systems and then match the data with accounts they have success with. However, a predictive model goes a step further by incorporating first-party data such as but not limited to, website visits, resources accessed, and content downloads. When combined, intent data and predictive analytics can help companies narrow down a target list of 10,000 individuals to a 100-person list based on their buying intent.
Major Benefits of Predictive Analytics
Let’s go a step further by describing some significant benefits that can be gained from leveraging predictive analytics:
- Gain a competitive advantage
- Find new product and/or service opportunities
- Optimize product and performance
- Gain a deeper understanding of buyers
- Reduce costs and risks
- Anticipate problems ahead of time
- Meet buyer expectations
An important question remains: If predictive analytics offer such an array of benefits, why is it not implemented universally across B2B marketing teams? If you think that using predictive analytics is a sure-shot guarantee for success, you need to learn more because there’s a noteworthy twist to it.
Major Pain Points to Consider
Put simply, predictive models are as good as the data fed to them. Predictive analytics provide a concrete direction for marketers, but relying too much on it can mislead sales teams and even impact a company’s overall ROI. One of the few flaws regarding predictive analytics is that it depends on past events and past data in order to predict the future.
It’s worth noting that a marketer can increase the probability of gaining conversions by using predictive analytics. However, it doesn’t provide insights into a few key parameters listed below:
- Competitors your prospects are engaging with
- Content your prospects are consuming
- Your target audience’s interests
- Volume of data transactions
In general, developing an efficient predictive model takes time, and they don’t produce results right away. This is one main reason why marketers are at risk of using up their resources on something that doesn't give them effective and nearly immediate results. On top of this, companies can’t rely on predictive analytics alone.
If customers are satisfied with their current product or service, but are still looking for a better offer, predictive analytics won’t be of much help in this area since it cannot cannot detect this kind of shift.
Predictive Models Need Intent Data to be More Effective
Furthermore, predictive analytics can be compared to looking at the world through a crystal ball. Whereas, intent monitoring is like looking outside the window and witnessing what’s happening in real-time. By leveraging intent data, companies can sense the probability of a specific event occurring in real-time before it happens. Like predictive analytics, intent data doesn’t depend on complex models and algorithms.
Regarding intent monitoring platforms like Anteriad’s, intent data can be gathered by tracking the online behavior of various prospects. They monitor data through the following avenues:
- Keywords that prospects search for
- Types of content that prospects read
- Various resources that prospects download
- Different websites that prospects visit
Gathering the information mentioned above can reveal the demographics and firmographics of different prospects, which makes it easier to decide if they fit into a defined buyer persona or not. When they do fit into a specific persona, the intent monitoring platform includes them in a target account list. When brands use other models, they receive leads in the form of quantity. However, when using intent data, brands receive leads in the form of quality, which is much more valuable and sought-after. At the end of the day, the quality of data matters more than merely the quantity of it.
Fortunately for B2B marketers and businesses, intent data is known to help find prospects who are sales-ready. Intent data also helps various teams learn the following key points:
- Who browses content related to your company’s product and services
- When did individuals browse specific content
- How often do individuals browse specific content, and how to contact them
All in all, predictive analytics need strong intent signals in order to reach their full potential. That’s one main reason why we at Anteriad stand by the phrase - “Discover Intent today”. If you’re ready to grow your business with the use of actionable intent data, sign-up for a free trial today!
