What is B2B Intent Data?
B2B intent data indicates the leads or accounts which are actively researching a line of products online. Seeing numerous people research a specific category on a product hunt page will indicate that there is a need for a solution. Following the thought, having the chance to pinpoint several people researching the same topic and being able to trace them back to the same organization can give you signals about the company’s readiness to go through with a purchase decision. In other words, it provides the most accurate prediction of who is in the market for your product. Intent signals are used to tip off sales teams when their leads might be ready to buy a solution they offer.
The technical collection of B2B intent data is established by finding peaks in research activity for any given product. Linking individual research signals from multiple IP addresses and cookie ID’s to the same organisation will provide a holistic understanding of the company’s intent. We see companies often utilising intent data in their account based marketing, targeted advertising, and demand generation programs. When used correctly, prospect intent data can increase sales and conversions rapidly.
How to use B2B Intent Data?
Purchase intent can tell when a lead is warm for outreach. Being merely used by sales and marketing teams, intent data has its home in the growth scene. Understanding the prospect’s online research behaviour equips you with insights that lead to relevant messages, at the right moment.
Sales teams can use intent signals to prioritise their efforts. Calling prospects at the right time will help sales teams to drive conversion and sales. Marketers can use prospect’s intent to understand the context and pain points of their audience. This further helps them to optimize their advertising efforts for more personal, relevant and timely messages. Connecting leads with intent data can even be utilised to automate sales and marketing processes. Email series and advertising campaigns can be launched with triggers based on specific intent signals.
Why is B2B intent data important?
Depending on the business and its goals, intent data can have various use cases. In general the data type is sought after due to its direct impact on sales and marketing efficieny. Here is a list of the most common use cases:
Intent signals help to differentiate between in-market and low priority leads. Seeing a lead actively search for products like yours will indicate a strong signal about buyer readiness. Combining this with the context, you can evaluate whether they match your ideal customer profile.
Marketers can set up automated outreach processes based on certain intent signals. For example, a series of emails or advertising campaigns can be sent out automatically after a predefined amount of research signals have been captured from a prospect organisation.
Content strategists can use intent data to better understand which content appeals to leads, and what still needs further optimization.
Personalization of Outreach
A deeper understanding about topics and content that is being researched by the leads gives sales agents more tools to make their communication more personal and develop closer relationships with their leads. For example, a sales agent can take topics based on data and mention them during outreach calls to capture the prospect’s attention.
Interest does not always translate to intent. With intent data you can separate the people with real purchase intent from audiences that are merely based on interest. This enables you to create more granular advertising strategies for prospects in various funnel stages.
Targeted Account List
While intent data can be used to enrich your existing lead lists, you can also use the dataset to build new lists of high quality leads. You can compile lists of accounts who are interacting with third-party sources regarding relevant topics but are not yet engaged with your company. By doing so, your sales teams can approach qualified leads which they could have otherwise missed.
Analyze and Retain Customers
Intent data can be used for customer retention as well. Keeping an eye on what your clients are researching will give you insights about their next moves. Are they considering to switch to your competitor? Perhaps there is a chance to up-sell something to them? Using data in your customer retention programs helps you anticipate and solve problems even before they occur.
What are typical Intent Data attributes?
Intent type - Explains the type of category/topic the intent is for. (e.g car, washing machine, software)
Intent signal strength - Measures the strength of the intent signals based on context. (Separates intent from interest)
Intent timeliness - Indicates the recency of the signals collected. (e.g recent, last week, or a year ago)
How is Intent Data typically collected?
Intent data is collected based on online research activity and content consumption metrics such as page views, email opens and white paper downloads. These metrics are aggregated from thousands of B2B websites and media publishers which capture visitors engaging with their content. Third party data providers combine the metrics from those websites in order to form intent signals for your use. Additional metrics on engagement such as dwell time, likes, and scrolls are used in combination to make sure the reader is actually consuming the content and not quickly skimming through the website. This enables for classifying the intent signals by their strength.
All individual intent signals are linked back to prospect companies via Cookie ID’s, IP addresses, Page URLs, Referrer URLs, operating systems, and browser language attributes.
How to assess the quality of Intent Data?
Like with most data types, the key to evaluating data quality starts with understanding its sources and collection. Try to understand the sources by looking in to what kind of content are the intent signals based on, what are the triggers for the signals and what is the signal strength based on. The next thing to investigate is the timeliness of the data you are acquiring. Recency of the dataset makes sure that your leads are “hot” and have not lost their intent before your outreach.
Once you feel convinced your data provider is able to provide you with recent data from quality sources, the next step is to ask for references. Look for customers who have used this data from the same vendor earlier and see how they have benefitted from it. Lastly, test the data. Depending on their pricing models, many vendors offer data sets and trial periods for testing purposes.
How is Intent Data typically priced?
Data licensing (monthly, quarterly, yearly) - Gain access to the aggregator’s data pool by paying a subscription fee.
CPM/CPC/% of Media - Pay per usage models offer you more control and are easily implemented to your ROI calculations.
CPL (Cost per lead) - Pay per lead models offer an easy way to benchmark the costs of data acquisition to the performance of your sales funnel.
Customized - Many data providers offer also custom solutions based on their customers needs.
What are the most common problems when acquiring Intent data?
Problem #1: Bad Fit
Having someone in the market for a solution does not necessarily mean that they are a good fit for your product or service. This problem stems usually from the lack of information on context provided within the intent dataset. Make sure that your data vendor is recording the context of the intent signals properly to avoid this issue.
Problem #2: No Intent
Not all interest means intent. Reading an article about helicopters does not necessarily mean that you are ready to buy one today. This issue is directly related to data quality. Some times buyers end up investing in datasets that record large scales of data based on interest but that fail to weed out the ones without actual intent. Understanding your aggregator’s data collection methods comes highly important if you want to avoid buying data without intent.
What to ask from your Intent Data providers?
- Ask your provider to describe the source(s) of the Intent data and elaborate on the specific data points that they collect.
- Make sure the data aggregator gives out the number of daily interactions they monitor consistently.
- Ask your vendor to explain how they link identifiers such as IP addresses to company domains.
- Ask for third party customer references with contact information.
- Make sure the dataset your provider offers can be integrated with your current sales and marketing technologies.