Marketers must reach shoppers who are in-market, not just browsing. Purchase intent is when a consumer expresses an actual desire to buy a product through their behavior, yet confusing “interest” with “intent” can be a stumbling block, shares, Daniel Heer, Founder & CEO at zeotap.
Amazon Prime Day, Cyber Monday, Black Friday — these are all days when online shopping gets a lot of hype and attention. Of course, online shopping takes place every day — millennials, for example, are making 60% of their purchases online in 2019, up from 47% in 2017 according to a CouponFollow survey. Most brands know that Q4 accounts for 30-40% of annual spend (Source: IAB’s 2018 Internet Advertising Revenue Report) and with Q4 right around the corner, planning is starting now.
Marketers need to reach shoppers who are in-market and not just window shopping. That is often a struggle — in 75 percent of e-commerce website visits, the customer leaves without buying anything. (Forbes, 2018).
Purchase intent is when a consumer expresses an actual desire to buy a product through their behavior rather than just demonstrating vague interest. Purchase intent data directly address the bottom of the marketing funnel, where chances of getting to a “yes” are at their highest.
However, the common strategy often adopted by advertisers — relying on product page views or “phoning it in” with demographic data — has proven ineffective. Confusing “interest” with “purchase intent” has long been a stumbling block, not to mention the problem finding trustworthy and fresh data sources.
Note that the focus here is on B2C marketing because B2B buying decisions are an entirely different animal. B2B buying (e.g. enterprise software) requires a much longer consideration process and prolonged account-based marketing efforts. B2C marketers have a much smaller window to reach in-market consumers. Of course, even in B2C, there are different timelines in the purchase intent journey (e.g. buying a sweater vs. buying a car). That has to be reflected in how the data is handled.
To evaluate purchase intent, marketers typically use predictive modeling to calculate future behavior based on historical data. However, marketers need more—they also need insights into “in-the-moment” customer activity.
Google calls these “micro-moments” and reports that 82% of smartphone users say they consult their phones on purchases they’re about to make in a store. If you’re a marketer — especially a competitor —you want to be all over that consumer with targeted ads or offers. That’s a moment in time that marketers want to capture immediately.
In addition to listening for micro-moments, marketers should be focused on other high purchase intent channels. Search is well-known as one of these because a user is actively seeking something out as opposed to just seeing or clicking on a display ad out of curiosity. Email can also be a decent indicator of purchase intent (or at least brand loyalty) because these consumers have volunteered their email addresses. Purchase intent can also be gauged by how far someone delves into your website. Are they just browsing or have they actually left something in a cart as they shop around?
Purchase intent marketing is not a socio-demographic game. Google’s research shows that marketers who try to reach their audience solely on demographics risk missing more than 70% of potential mobile shoppers. For example, 40% of baby product purchasers live in households without children. These buyers could easily be relatives or friends shopping for a baby shower.
Marketers need to be able to process large volumes of data effectively and convert that into real-time, actionable insights. Yet there’s a good chance most marketers aren’t confident in their data sources.
According to a joint study by Bazaarvoice Advertising and Ad Age in 2017, nearly two-thirds of marketers are not entirely clear on the origins of the data they employ in their ad campaigns and three out of four marketers are not fully confident that the data they’re using reaches “in-market” consumers. The study also found that 64 percent are not fully clear on the origins of their data sources.
Furthermore, nearly one-quarter of brand marketers and agencies don’t know how often their data sources are refreshed. Only fresh purchase data can offer an accurate picture (one example is when items have been recently placed in a digital shopping cart), or through geo-fencing when a consumer is near a Starbucks or Target, for example, and has that app opened.
Note that marketing affiliates companies can be useful partners when it comes to in-the-moment purchase intent because they track when users read an article, click on a link within that article about a featured product and can redirect them to an e-commerce site to hopefully make a purchase.
To truly harness purchase intent, marketers need more user insights which can include socio-demographics, app usage, type of channel (search, email) and past purchase data to get a 360 picture of each consumer at that moment.
Let’s stop relying on siloed, out-of-date data that only reveals one dimension of user behavior, but rather let’s start putting together different data points that aggregate holistic and dynamic behaviors. Only then, brands will be able to determine if there’s truly a purchase intent behind each one of them.