When it comes to eCommerce analytics, the buzzwords are by now well-worn. Say a merchant needs to develop a “360-degree view of the customer,” and she’ll likely respond, “Yeah, yeah. Tell me about it!”
As many have discovered, while the goal of understanding consumer behavior across touchpoints is worthwhile, the means to achieve that goal remain elusive. Despite a burgeoning array of big-data tools and social listening platforms feeding ever-more-complex recommendation algorithms, merchants are still struggling to derive the meaningful insights that lead to more satisfactory experiences for shoppers — and, in turn, earn more revenues and loyalty.
In 2016, just 41% of digital marketers participating in an Adobe/eConsultancy survey agreed that they have the staff and technical capabilities in place to collect the right data and put it to good use. And shoppers report that clumsy efforts to wield data erode confidence in merchant brands: 23% of shoppers said they were put off by “incorrect data” in personalized messages, while one in five reported receiving promotions for products they’d already purchased.
And yet, it’s clear that merchants must forge ahead in their quest to better understand shoppers’ needs regardless of where and how brand interactions occur. Shoppers no longer distinguish between siloed channels when searching for products and services online: for example, 43% of consumers say they favor retailers offering consistent service online and offline, and overall, more than half say it’s important for merchants to recognize them across touchpoints and tailor content and offers accordingly. Merchants must adapt their organizations — and metrics — to match these expectations.
Furthermore, better tracking across touchpoints can help justify investment in online initiatives that don’t necessarily result in direct online sales. After all, fully 51% of all retail sales are set to be influenced by the Web this year — dwarfing the 11.8% of revenues directly generated by online purchases.
For these reasons, merchants would do well to focus performance measurement initiatives on uncovering the metrics that illuminate and quantify the Web’s broad sphere of influence over offline shopping activities. Among the tactics to consider:
Scrutinize attribution models closely. It’s tempting to set percentages to apportion credit for online revenues among the marketing touchpoints that preceded a sale as a means of capturing indirect influence — and indeed, such models are an improvement on “last-touch” attribution that credits only the source that directly referred the sale. But modeling is still far from perfect, as biases among target audiences can skew results. Merchants would do well to scrutinize attribution results closely, adjust as necessary, and use the models as just one factor when determining where to invest marketing dollars.
Map and market to store influence zones. Marrying online behavioral data with geographic input relative to store locations has the potential to wield significant insights, as merchants can track usage of features such as “buy online, pick up in-store,” and “reserve online, buy in-store” and determine the size of the zone influenced by store locations as a result.
While it’s tempting to allocate revenue based on this modeling, such an exercise is likely to prove a zero-sum game: after all, just as store outlets deserve credit for handling fulfillment activities for online purchases, the eCommerce site can help spur additional store revenues when shoppers visit to pick up items bought on the Web. Rather than split hairs over which silo gets how many dollars, merchants would do better to use store-zone performance to influence geo-targeted marketing offers and messaging.
Understand in-store usage of online assets. As discussed previously, shoppers rely on their mobile devices to conduct in-store research — so merchants would do well to identify and report on this distinct activity in order to justify investment in technological upgrades such as in-store wi fi, tablet apps for sales associates, informational kiosks, location-specific downloads and coupon offers, and even beacons and geo-fencing tools.
Standardize and measure customer service across touchpoints. Traditional call center metrics must be modernized to account for increasing usage of live chat and social media for customer service, so that successful practices can be identified and shared across the organization. Usage of self-service customer service tools, such as FAQs and Q and A features, should also be factored in.
Recognize loyalists and advocates. To uncover usage patterns among repeat customers — and encourage more buyers to return — merchants should track redemption of loyalty points or perks online versus offline and on mobile devices. Similarly, referral programs that reward (and track) both the referrer and the recipient of the referral can help merchants identify and serve segments of customers who deserve tailored VIP treatment.
Invest in identity matching tools and test continually. While the much-vaunted “360-degree view of the customer” remains elusive, merchants should do their utmost to unite disparate data sets and stay at the vanguard of innovation when it comes to identity matching. Continual testing, analysis, and adjustment to third-party tools will help put the holy grail within reach.
Add omnichannel metrics to routine analytics reporting. If they haven’t already, merchants should expand their performance dashboard to include metrics that go well beyond conversion rate and revenue. Among the data points that should be collected and segmented by screen size and location:
- Use of inventory lookup via the eCommerce/mCommerce site and app
- Use of “buy online, pick-up in store” and other in-store fulfillment options
- Online registrations for in-store events, personal shopper appointments, and the like
- Browsing, cart additions, and purchases occurring within store locations
- Online orders placed via employee point-of-sale apps or tool in stores
- Use of the “save cart” feature to move between digital touchpoints
- Use of the “print cart” feature
- Use of “like” and “share” buttons from product pages
- Email signups from the Web site, social media, and app
- Mobile app downloads
- Usage of stored payment data within apps or the mobile site
- Usage of alternative payment methods
How are you measuring performance to reflect today’s omnichannel reality?
