Every day, we are confronted with the state of retail. Either with news of chains filing for bankruptcy or empty windows in the high street. Observing consultants easily point fingers: sometimes at the digital race to the bottom, sometimes at the old-school process in which customers embark on something that more closely resembles order-picking in a warehouse than being wowed in a modern shopping experience. Turns out, there is an easy way to bring customers into your (online) stores: by leveraging your offline assets, online.
As Eric Schmidt likes to say, ‘revenue solves all known problems’. For an omnichannel retailer, this means understanding how the customer experience online, on the phone and offline helps your customer when purchasing your product. Unfortunately, this usually doesn’t happen, as a channel’s sales steer the respective organisational silo. Many large companies treat their customer-facing channels as rivalling brethren, expecting that competition will bring better results than shared targets.
Whose channel wins?
This was no different at the Telco, where my team’s assignment was to – within three years – quintuple the digital acquisition and octuple the digital upgrade share of total revenue. A zero-sum game, one might think, since increasing online sales would presumably decrease offline ones.
But is it really the case that this growth can only come from the offline channels? And if we are only compensated for growing online sales, why would we bother to track offline sales coming from online searches? We decided to find out. We performed a test to measure the effect online ads had on offline sales. What we found out? For each online sale, there were five sales happening in stores after shoppers clicked through the same Google Ads in their search. Instead of being a case of ‘mix shift’, we were discovering a new mix. If we were not online with our ad, one out of every five of those offline sales would not have happened. Read more about how we did it in this Think with Google article.
Why local matters
Blown away by the amount of converting footfall that we were driving, we analysed the omnichannel journey we had created. The consequences of siloed target-setting quickly became apparent. Since the digital team was only compensated for online sales, the online-to-store journey was neglected to say the least. We were not indexed on any of the customer’s local generic searches on Google. The paid ad pointed to the homepage. We served persevering customers searching to find a store nearby with a map, store hours and a phone number. In a dynamic page. Thus non-existent for Google’s crawlers.
According to an internal Google deck, 46% of searches are local. People looking for the store around the corner, not the big mammoth corporate office. Neglecting local search is the same as being closed for business for one in every two people searching for us. Let that one sink in for a minute.
These discoveries led to even more questions. Put aside the fact that we were ignoring almost half the market. Were we at least satisfying the remainder of consumers with relevant local content? Finding directions and opening hours are merely means to an end, which is either getting service or finding a product. So why are we not showing the products that are available in that store? We saw that it was connected to those rivalling brothers putting mutually exclusive claims on customer. If “buy online” would be served on the store page, the local rep would miss out. When the customer rings, the in-store cash register won’t. The number-driven economy at its finest, leaving the customer to decide at the cross-channel crossroad.
Knowing the ROPO (research online, purchase offline) effect and discussing this with the area presidents responsible for offline sales, we found mutual ground. What if we could steer our online budgets on omnichannel sales? That would give David the slingshot to hit Goliath between the eyes. What if we would show customers the stock of that white Pixel 2 128 GB in the stores nearby? What if we would let them order online and pick it up in store? What if customers could plan an appointment – or even join the queue – online? What if, as marketers, we could track all of this behaviour? It is the omni-potent dream of every sane click&brick retailer. But how could we realise it?
The click that made it tick
Ingredients for this omnichannel experience are: store information (lat-long, address, etc), product feed, local inventory feed, appointment API. Turns out we had all this. What we did not have was a platform that scaled content, adapted to various aggregation levels of customer intent, and was designed for any device. We also didn’t have the bandwidth to build it in-house. Our local partner at the time understood the dream, but could not deliver much more than the disappointing current experience. Enter a New York City start-up that could. They ingested our feeds, analysed local search behaviour and converted it into a page hierarchy and taxonomy that made sense. They presented designs that still make our e-commerce site jealous. Sometimes, it is just better to start from scratch outside the monolith, using microservices that connect it to the mothership to ensure the data presented is accurate.
This boom could be yours
Within two months, we were live on 1,000+ stores, creating a plethora of microsites with pages for all products and services we offered locally and delivering on the aforementioned omnichannel dream. Google organic rankings quickly increased, paid media increased click-through rates by adding local inventory in the ads. Within nine months, we were break-even. A year later, we rolled out to all ~10,000 stores with increasing triple digit ROI through increased traffic and increased conversion rates, both online and offline.
Beyond the monetary success, we took pride in the fact that the customer’s intent was now understood and served with contextual content to reach the goal, which translates into higher NPS and loyalty. And that’s where any aspiring company should start. Freed from corporate siloes, egos and org charts.
Main image credits are for: Dieter de Vroomen.