All companies start because they have a new or improved solution to a problem experienced by a particular market segment. As soon as a potential buyer begins looking for a solution to their problem, they embark on a buyer journey.
There can be thousands of permutations of ways in which a buyer journey can take place. This is especially true for online journeys - where it can be extremely difficult to know exactly what stage the buyer is at, especially because they are often anonymous (in other words, not known to your identity/ABM tools).
The best way to determine where they are at in the buyer journey is to accurately gather and analyze intent signals.
According to GE Capital Retail Bank’s second annual Major Purchase Shopper Study, 81% of potential buyers research products online before buying and spend on average 79 days gathering information for major purchases.
Now is the perfect time for your marketing team to gather their very own first-party data or apply existing third-party intent data to identify website visitors who are more likely to buy your product or service.
Let’s explore in detail what intent data actually is, how it is collected, how it helps sales teams achieve their targets, and how you can easily automate it today.
What Is Intent Data?
Intent data is data that shows, in aggregate, who is looking for (has buying intent) either a particular solution or a solution that solves a particular need.
It’s possible to determine buying intent because website visitors leave a trail of data, such as online search results, time spent reading articles on a given topic, requesting demos, sending emails to customer support, etc. In fact, by the time potential buyers directly engage with sales teams, they have to a large degree, already made up their minds.
There are three types of intent data available to marketing teams:
- First-party intent data refers to behavioral information that your own tools were able to gather from your own website (and other products or online properties). This is the best kind of data, although it can be hard to obtain at scale.
- Second-party intent data is much less popular because it requires you to commission data gathering to another company that specializes in that type of research (essentially buying someone else's first-party data).
- Third-party intent data is an aggregate of millions of data points gathered across the web and is used by most buyer intent data solutions. The problem with this data is that it can often be outdated, incorrect, or irrelevant. Another problem is that your competitors might also be buying this data.
How Marketers Gather Intent Data on Customers
Most commonly, marketers will engage third-party intent data solutions to gather intent data. Third-party intent data solutions continuously collect data from online aggregators, forums, news, B2B portals, ad platforms, customer service chats, search information, and more.
However, as mentioned, these third-party intent data solutions often contain data that is outdated, incorrect, or irrelevant.
Knowing that someone is searching for “productivity software” might reveal some intent, but how is that weighted? Was it truly a purchase intent signal or was it an informative/educational one?
Another big problem with third-party intent data is the fact that it’s not updated in real-time as the visitors browse your site.
It can still be helpful, but to make it really work you’ll need first-party buyer intent data (more on this soon).
How Intent Data Helps Engagement & Marketing Insights
Intent data can be valuable for sales and marketing teams of all sizes. It can inform various marketing strategies, help segment the audience, and encourage personalized outreach to selective contacts.
Unlike other types of data, intent data is predictive of potential buyers. This opens a proactive path for your team, so they can:
- Identify buyer intent. See which companies and potential customers are really interested in your offering.
- Personalize ads. Spend your marketing budget more effectively knowing who you’re targeting.
- Score leads. Rank your accounts and save time by only reaching out to companies that match your criteria.
Often, it’s the first salesperson who wins the business. The predictive element of intent data thus gives you a valuable opportunity to get ahead of your competition.
How to Automate Intent Data Processing & Get First-Party Intent Data
Having high-quality intent data can revolutionize the way your sales and marketing teams work, making them more efficient and more productive at the same time.
Since no one can manually keep track of all the intent data available, the most important productivity gain you can get comes from outsourcing and automating the collection and analysis of your audience’s buyer journeys and associated intent data.
But, what if you could not only automate the capture and processing of this data, but also do it in real-time with your very own website visitors?
Lift AI is the only platform that applies the latest advances in artificial intelligence and machine learning to identifying buyer intent of every single visitor on your website in real time.
To be able to analyze website visitors with such accuracy, Lift AI leverages over 15 years of sales data gathered across multiple industries, with billions of profiled visitors and over 14 million analyzed conversations codified into the model.
As visitors navigate your website, Lift AI assigns a ‘buyer intent’ score. This score is based on the visitor’s historical actions and their real-time behavioural actions on the site, which gets updated on the fly. Therefore, the intent data is first-party, unique to you and your website, and highly relevant and accurate.
High-scoring visitors can then be directly connected with an available BDR (sales rep) through the chat platform you already use (e.g. Drift or LivePerson). Medium and low-scoring visitors could be offered an automated chatbot experience or a self-help guide instead.
As a result of such segmentation, Lift AI customers improve their chat conversions anywhere from two to 10 times in 90 days. For example, PointClickCare increased conversions four times with Lift AI, whereas Formstack’s pipeline grew by 88%.