In the past few years, buyer intent data has seen a drastic spike in both popularity and importance. As more companies switch to online B2B sales, they find out that having actionable data at hand related to how likely their website visitors and leads are to buy is critical.
When you have accurate buyer intent data, you can create tailored marketing campaigns, personalized follow-ups, and captivating content that is interesting to your audience and address any issues and doubts that prevent them from buying.
You can also segment your website visitors or leads by buyer intent, prioritizing those with the higher chance of converting. This way, your BDRs can focus solely on high buyer intent leads and significantly increase their sales as a result.
So what is buyer intent data exactly? Where should you source it? And how can you use it to sell more?
What Is Buyer Intent Data?
In 2020, there were 40 times more bytes of data than stars in the observable universe, measured in quintillions — and the pace of data creation worldwide is still accelerating exponentially.
Even though 99% of all data online is not useful or actionable for your company, a lot of the remaining 1% could be if it’s aggregated and processed correctly.
In essence, buyer intent data consists of interrelated data points that can be used to tell a story about a particular online user. For example, if someone searches for “CRM for small businesses,” then visits the top five CRM vendor websites and requests a demo in two of them, we can conclude that their buyer intent in relation to CRMs is high. If your company sold CRMs, this is definitely someone you’d like your BDRs to prioritize in their pipeline.
However, this is a simplistic view of buyer intent data. It’s not enough to just consider one or two points of data to infer the buyer intent of a visitor. An accurate representation would need much, much more data.
Buyer intent data can come from a variety of sources including websites, search engines, social media, targeted advertising, content consumption, and more. Even real-life buyer intent examples from conferences, presentations, pitches, and meetings can be included, and are usually recorded in your CRM.
When it comes to specific actions, we now have the ability to record more than ever before: keystrokes, Google searches, website browsing patterns, video plays, clicks, and much more. In analyzing such data, buyer intent tools pay special attention to recency, frequency, and engagement.
Leveraging buyer intent data in sales can deliver a major boost to quantitative and qualitative results, both expanding the reach and improving the targeting. The process of using such data starts from sourcing — that’s where the distinction between first, second, and third-party data becomes critical.
First-Party Buyer Intent Data
First-party data relates to what you can gather internally. This is the data generated when someone visits your own website or contacts you, for example, or when you conduct your own customer research. Your BDRs also generate first-party data through their efforts, which they usually record in a CRM.
It’s generally accepted that first-party data gives you the most accurate and actionable results, as you can dial the precision of that data right up to your required specifications and refine it as you see fit. You can also act upon your first-party data immediately, before it becomes outdated, which positively differentiates it from other data gathered elsewhere.
Moreover, a lot of first-party data is refreshable in the sense that customers come back and improve upon previously recorded information.
So first-party data is the most affordable and reliable type of data, and is the easiest to convert.
There are two general issues with first-party data. First, you have to be sure that the data you’re gathering comes from your ICPs (ideal customer profiles)— otherwise you’re collecting information that is not as relevant to you. Second, generating lots of first-party data is hard because you’re essentially limited to your ad budget, website visitors, and BDR efforts.
Second-Party Buyer Intent Data
You generally won’t find too many mentions of second-party buyer intent data. While it’s the most rarely used type, it has its benefits too.
Second-party data is basically somebody else's first-party data. It refers to the customer behavior information you’ve bought directly from someone else. You can get second-party data from partners, affiliates, and certain data providers or researchers that gather their data themselves.
Examples of second-party data sources that include buyer intent data are G2 and TechTarget. The trick is to ensure that the data is inline with your ICPs and are from a trustworthy, current, and reliable source.
Using second-party data is a great auxiliary way to expand your reach in the market, but it is also quite limited in scope compared to what third parties can provide and is somewhat less accurate than what you can collect yourself.
Third-Party Buyer Intent Data
As we’ve seen that data online is nearly infinite, it makes sense that there are numerous companies out there that don’t collect their own data but rather aggregate existing information and then sort and provide it in a digestible form. This is called third-party or external buyer intent data.
Third-party data comes from ads, cookies, IP addresses, databases, website crawlers, chatbots, media mentions, etc. Analyzing all of this together allows companies to create a holistic view of any particular customer’s behavior. While with first-party data we can only see potential customer actions on our own properties, third-party data can tell us what they had done before they came to our website and after they left. So it can be used to augment our own accurate first-party buyer intent data in interesting ways.
Besides, third-party data gives us access to a much wider audience and helps us source new prospects on a completely different level. Think thousands of leads instead of dozens.
A major downside with third-party data, however, is its integrity. Lots of information might be already outdated or inaccurate by the time you get it, which makes its targeted use much less effective.
How to Use Buyer Intent Data
One of the biggest challenges in marketing and sales today is trying to scale first-party data while increasing precision of third-party data at the same time, and then merging the two to calculate buyer intent for best results. This is the exact approach that Lift AI has been pioneering for years now.
Lift AI is the first solution to effectively integrate first and third-party data to gauge buyer intent for every single visitor on your website.
Based on a proprietary machine-learning model, Lift AI has processed more than one billion third-party data points and 14 million live sales engagements to make accurate real-time buyer-intent predictions.
As a result, Lift AI determines the buyer intent of any visitor to your website, even if they are completely anonymous and haven’t been recorded in your CRM (up to 98% of them).
Lift AI can do so because it leverages visitor's direct actions (first-party data) but was trained on an extremely-large volume of previous web interactions collected from 15 years of profiling visitors on a network of websites. On average, Lift AI finds the highest buyer intent visitors (about 9% of the overall traffic) with 85% accuracy.
But that’s not all. Lift AI integrates with your enterprise chat platform and after it assigns a score to every visitor, it’s able to segment them further, sending the highest-scoring ones directly to chat with your BDRs, while connecting medium and low-scoring visitors with a nurturing bot or a self-help guide.
The outcomes reported by active customers speak for themselves. Lift AI is able to grow chat conversions anywhere from two to 10 times within the first 90 days.
Finally, there’s a viable solution that can integrate first and third-party buyer intent data in one place, in seconds, and make it actionable by working directly with your BDR team.