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Categories: Marketing, Sales, Technology,

Intent data is arguably the newest and hottest B2B buzzword right now. Together with groundbreaking emerging technologies like Artificial Intelligence (AI), intent data offers a fresh, exciting tool for B2B Sales and Marketing to identify their ideal audiences, and particularly to predict when the time is right to engage them.

We’ve defined at length what exactly intent data is in a previous blog post, but just to summarize: Intent data is data gleaned from online activity which indicates an interest by users in one or more “topics”. If the topic/topics relates to your company’s offering, and if the user showing interest falls within your ideal customer profiles, that could indicate that they are ready to buy.

But at a time when many B2B Sales and Marketing organizations are already feeling overwhelmed by the volume of data they’re handling, adding another type of data into the mix might not seem like a natural choice. What’s more, since intent data is a very young, emerging data category, it’s hard to get concrete figures about success stories — which only makes it harder to understand its true value.

However, many B2B companies — particularly, though not exclusively, in the tech industry — are already using intent data to improve their Sales and Marketing performance.

Here are a few of the most common use cases of intent data for B2B Marketing and Sales:

1. Automated outreach

This is one of the most common use cases, and one we’ve covered before:

With the adoption of marketing automation platforms and lead lifecycle management, many companies are already using 1st party behavioral data to track progress within a lead scoring model.

This scoring model attempts to quantify the intent of the visitor based on a culmination of activities. For example, when someone visits the product overview page their lead score will increase by 5. If they visit your pricing page, indicating an even greater interest in buying, it will increase by 10, etc.

When that person’s score reaches an agreed upon threshold (or becomes marketing qualified) an alert is sent to sales to reach out to that person.

2. Sales prioritization

Adding intent data into the Sales data mix gives reps an extra layer of accuracy when prioritizing which leads and accounts to go after first.

Assuming Sales already have accurate data on who their prospects are, intent data helps them to know when is best to reach out. This improves sales efficiency by minimizing the time wasted on cold leads.

3. Personalized marketing campaigns

Today’s B2B customer, like their B2C equivalent, expects your company to talk to them as an individual. That personalized marketing is considerably more effective than generic pitches is by now taken as a given.

Intent data helps you run more personalized email and direct mail marketing campaigns by gaining insights into which prospects are interested in relevant topics right now.

For nurture campaigns, 1st and 3rd party intent data can be used to identify potentially qualified prospects already in your databases who previously went “cold”, but have recently shown resurgent interest in the relevant topics. Such prospects are ideal candidates for effective nurture programs; armed with that information Marketing can know who to target, and what topics will most likely engage them.

For outbound marketing campaigns, 3rd party intent data can flag up net-new accounts showing enough interest in the right topics to be considered a good-fit prospect.

4. More accurate ad-targeting

Similarly, intent data can be used to provide an additional layer of accuracy to your online ad campaigns.

5. Account-based marketing (ABM)

Intent data can provide significant value whether or not your company is running ABM campaigns. However, it’s clear that the above use cases can be used effectively to help build accurate target account lists, for all of the above reasons.

6. Predictive scoring

The power of predictive marketing technology relies to a great extent on how much quality data is being used. “Quality” in this case means both accuracy and relevancy — knowing that your Marketing/Sales databases are up-to-date isn’t all that helpful if the insights you have are superficial and don’t tell you much about your target audiences.

For that reason, intent data can be a useful additional kind of data to use when building predictive models, by providing further insights into how likely a prospect is to buy right now.

Learn more about intent data, including how to use it to improve engagement and conversion rates — download our free white paper:

Timing is Everything: 6 Ways Intent Data Can Help B2B Sales And Marketing

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