Google has just rolled out a new search feature using crowdsourced data to warn users about busy restaurants. Marketed as an aid for diners to avoid long lines, we at WhatsBusy wonder how pleased restaurants will be with the inaccurate results.
We know that Google wasn’t sold on this approach in the beginning. With about 40% of US mobile device coverage and less than 100% mobile geopositioning accuracy, predictions of crowdiness at restaurants will not be accurate. No doubt Google weighed their accuracy concerns against the difficulties of working with reluctant restaurants and decided to launch.
When WhatsBusy started four years ago, we set out to improve the lives of both the public and the businesses. The public would accurately know when places were busy or not, and businesses would be given insights using their own and external data to help them compete and thrive.
Unfortunately, after four years of solid work and respectable progress, I can attest that brick and mortar businesses – especially restaurants – continue to be pushed aside and fall behind. Understandably, restaurants are focused on running their daily businesses and new initiatives come and go. But the bigger issues won’t go away. Most importantly, the economics associated with a restaurant customer are not favorable for innovation. Innovators must decide where to sell their invention. If any such innovator targets restaurants, he will painfully discover that restaurants pay 1/3rd as much as their enterprise counterparts and take nearly THREE TIMES as long to make purchasing decisions. This represents a near 9x revenue risk for the restaurant vertical, and quickly convinces the innovator to look elsewhere. Before long, word gets around.
With these sorts of issues plaguing the industry it’s no wonder that Google launched their new, but still inaccurate, feature the way they did. Given empirical evidence for how slow brick and mortars move, Google made a judgment call. Not unlike Apple, who launched Siri knowing that 30% of spoken inputs were unrecognizable, Google opted for less-accurate mobile data as opposed to working with the reluctant businesses they would project.
Brick and mortars, especially low margin restaurants, should be very concerned. The actions of a giant innovator have just implied that they will work around you, not with you, because you’re too hard to work with. And if you really do think about it, there are numerous solution providers whose actions have said the same thing: restaurants don’t have advanced forecasting; they aren’t able to monitor promotion performance; they don’t have centralized data management platforms or customer databases; they are not using their suppliers’ free analytics to drive lift and lower procurement costs; and they don’t even employ meaningful benchmarking. All of these solutions are widespread in other verticals.
It’s scary times when Google and external players know more about brick and mortar businesses than the businesses know about themselves, and even worse that they will be sharing inaccurate data with the public. This doesn’t need to be the final answer because operators have POS data. Sadly, however, most operators are unable to put it to work. For instance, McDonald’s and YUM, the two largest restaurant chains on the planet, cannot even tell you how many hamburgers or tacos they sold! Instead, these companies spend millions with marketing firms to maybe conclude how their promotions are working. Given the right data, a data scientist could do this in an hour.
Bottom line, Google’s new search feature should alarm all restaurants, but there’s also a silver lining. Yes, Google using mobile data to predict a business’ crowdiness will be inaccurate, and the merchant will lose more of that customer relationship. And yes, this might have the same negative impact that Google’s inaccurate listings data had on the Serbian Crown restaurant. But there is still enough time for operators to recapture what Google has taken. You can generate more accurate forecasts with your POS data and regain most of your consumer positioning, including collecting data on who’s looking at your business at what times. And if operators are willing to further open up their data, they will quickly benefit from all the aforementioned solutions that are quite common in other verticals.
Times are changing fast. Brick and mortars are now being pushed further back. They can catch up, but only if they make big changes quickly. Unfortunately past performance does not indicate this is likely. After all, how does the saying go, “The first step to fixing a problem is admitting you have one”? Maybe Google’s new search feature will convince them that there’s an even bigger problem at their door.
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