Asahi: Tapping into the beer-lovers of the future with the aid of AI
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Asahi: Tapping into the beer-lovers of the future with the aid of AI

Jessica Twentyman — February 2020
As it seeks to engage more directly with customers on social channels, the Japanese beer-maker has turned to Salesforce’s AI engine for help. And found the results “amazing,” according to Takeshi Tamate, deputy manager for digital marketing at Asahi Breweries.

Takeshi Tamate has worked for Asahi Breweries in Tokyo for almost 11 years, first as a sales representative and then as a founder member of the company’s digital marketing group, where he’s now deputy manager. During that time, he says, he’s sold a lot of beer, met countless customers and become something of an industry expert. But, he complains, “I still can’t predict the future.”

He’s joking, of course, but clairvoyance is just the kind of power he’d really value when trying to determine which marketing messages achieve the best sales results in Japan’s highly competitive beer market. And every sales interaction matters in the battle between the four dominant brands — Asahi, Kirin, Suntory and Sapporo — especially as younger drinkers are increasingly lured away by a wealth of alternatives, including alcopops (chūhai), whisky-and-soda highballs (haibōru), wine and cocktails. They are also an audience much more receptive to personalized online engagement than any kind of mass communications.

““Asahi Breweries' Takeshi Tamate”
Takeshi Tamate of Asahi Breweries

In place of a sixth sense, Tamate has instead turned to artificial intelligence (AI) to uncover the most effective digital marketing approaches. Along with his team, he has used’s AI-powered Einstein Analytics to interrogate Asahi Breweries’ customer database to help predict the most likely candidates for switching allegiance to his much-loved product.

The medium for such one-to-one messages, meanwhile, is Line, Japan’s most popular social media service. Line has around 80 million monthly active users in Japan, putting it well ahead of social-media imports such as Twitter, Instagram and Facebook. It was originally developed by Japanese web company NHN Japan (since renamed Line Corporation) as a disaster-response tool in the wake of the 2011 Tōhoku earthquake, providing a way for users to stay in contact with friends and family. Since then, it has expanded beyond instant messaging into digital wallets (Line Pay), ride hailing (Line Taxi) and music streaming (Line Music) — as well as providing tools that enable brands to promote themselves to users on its various apps and services, under the Line@ umbrella. Typical Line@ marketing tactics for companies include sharing announcements and coupons, conducting surveys and exchanging one-to-one messages with customers.

“Asahi Beer

While Line is a great fit for the demographic that Asahi Breweries wants to target, its use comes with considerable costs. “Line is a pay-per-use medium, so if we send a lot of messages, we have to pay a lot of money. That could be a dangerous [waste] and we don’t want that risk,” Tamate explains, who also plays wider role in promoting digital transformation across the company.

“I spend a lot of time analyzing customer data but I’ve realized that it’s impossible to do the most effective analyses using just human [capabilities]. What we need is the power of AI,” he says.

The pressing need to ensure that every Line campaign he conducts reaps the best results, at the least cost, prompted Tamate to run a proof of concept (PoC) with Einstein Analytics last year. The goal: to determine return on advertising spend, or ROAS.
Boosted conversion

Einstein Analytics is a collection of tools from that enables business users to surface predictive charts and figures from the data they hold in their implementations of the Salesforce customer relationship management platform. Within that wider toolset, Einstein Discovery then uses AI to guide the business user through facts and themes it has found in the data, enabling them to explore different variables and potential outcomes of a proposed strategy and tweak it accordingly.

So, in the case of Asahi Breweries, Tamate can investigate the likelihood of customers responding to a particular Line campaign based on their age, gender, location, the length of time they’ve followed Asahi Breweries on Line, their previous participation in the brand’s Line campaigns, and so on. From his explorations, an Einstein model is built that scores customers on the likelihood they’ll respond positively to a campaign and assembles an optimized ‘mailing list’ of targets.

Initial results have been impressive — certainly enough to keep Tamate and his team interested in using the Einstein tools.

“In a campaign run last year as part of the PoC targeting customers via Line, customers who were pre-scored by Einstein at 90 or above [very likely to buy] showed a conversion rate which was 18 times higher than that achieved by mass distribution to customers not pre-selected by the tool. Even those scoring far lower showed significantly higher conversion rates; for example, for those scoring between 60 and 70, the conversion rate was seven times higher than the baseline, unselected targets.

“These results to me were amazing,” says Tamate. “We are getting good guidance now on which customers to send messages to — or not. And that ‘or not’ group is important because we don’t want to send messages to people unlikely to respond. I’m a digital marketer, not a data scientist or engineer — but the results show that anyone, even someone without AI skills, can start to predict the future.”

• Takeshi Tamate was a speaker at Dreamforce 2019 in San Francisco.


First published February 2020
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