As we have spoken about in the past, data analytics has a major impact on marketing through the use of automation tools. By automatically inputting data from different vectors, there is a great amount of information to yield from a campaign as it’s happening, which can help marketers make alterations that increase leads and conversions without drastically changing course. The return on investment in assessing customer behavior is massive enough that many businesses use it now to direct how they promote and deliver products. One area where marketing gains a lot from analytics is behavioral-based strategies, and intent data is one of the foundations for those efforts.

Going in a specific direction
Business 2 Community explained that intent data represents a customer’s actions online. Instead of just following the transaction, companies can now follow where a user goes on the Internet. When marketers receive the recorded movements, they get a story out of what this person does while browsing. In other words, it identifies the patron’s intent or purpose.

The use of intent data is part of the greater shift to behavioral marketing. This practice, instead of simply following demographics and market tastes, takes the promotion to a granular level, assessing individual needs and desires based on what people do. In doing this, there is a greater potential of getting the customer’s attention.

Capturing customer intent can help shape how they shop.
Capturing customer intent can help shape how people shop.

Giving in to immediate demands
There are some good reasons to incorporate intent data into marketing strategies. The first is that marketers have the advantage of immediacy in their hands. If a customer looks to purchase something in the next 24 hours or even 10 minutes, a quick ad placement on key sites can possibly influence his or her decision. Marketing Land noted that an office furniture retailer received the majority of conversions within 24 hours of seeing its most recent ad. That’s a significant turnaround for such purchases.

Using intent data also helped establish patterns amongst individual customers that previous sources wouldn’t get with consistent accuracy. For example, the retailer discovered that many of its conversions occurred in the afternoon hours. With this in mind, the company reshaped its campaign so that ad buying occurred most frequently during those hours. The end result was a 35 percent increase in ROI. What’s more, the company didn’t even need to send out a coupon or supply a discount to entice customers. That kind of strategy expands on profit margins even more, and makes it easier to market without incentivizing consumers.

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