SAP : Intelligent Coffee Closes Gap In Experience Economy

The Intelligent Coffee Experience was among the most energizing (literally) showcases I visited during last week's SAPPHIRE NOW and ASUG Annual Conference. As welcoming as any neighborhood coffee shop, the prototype 'café' had shelves stocked with inviting bags of coffee beans, mugs, and pots with the real stuff on pour from a pushcart in front.

Matthias Aurin from Innovation and Experience Marketing at SAP quickly ushered me inside, where he explained how real-time information from solutions including SAP S/4HANA and SAP C/4HANA transformed the coffee drinking experience for consumers, as well as café owners and their ecosystem of suppliers.

Connecting information from fast-changing consumer demands through sourcing the right beans makes all the difference in brewing a great cup of coffee that also serves up generous revenues.

Solve Problems Before Things Go Wrong

It turns out a lot can go wrong when it comes to coffee equipment and everything that goes into a great cup of java, including water. Aurin showed me how a colorful dashboard immediately captured incidents like malfunctioning machines and filters, helping support reactive and proactive equipment maintenance for café owners. The SAP Analytics Cloud solution collected and displayed statistics on where problems were happening by equipment type and process across locations. Machine learning kicked in to surface correlations between the age or type of coffee makers, number of cups brewed within specified time periods, and hard water in certain locations.

With this kind of relevant data, suppliers could solve problems store managers didn't even realize they had, preventing machine breakdowns for minimal customer disappointment.

'When you can see there are other shops near particular areas with hard water, but that haven't opened up tickets yet, you can give them a heads up about changing filters before something happens,' said Aurin. 'In addition, the latest coffee machines can be connected so companies can use IoT data, applying predictive maintenance strategies. They can also automate maintenance services.'

Feedback Takes Guesswork Out of Product Design

Managers can swap old-school coffeemaker user manuals for augmented reality and SAP Conversational AI with a virtual assistant. Aurin demonstrated how someone could immediately identify problems with machines, order parts, and schedule repairs with SAP Service Cloud. After service is complete, companies could use Qualtrics to measure not only the maintenance experience such as technician expertise and repair speed, but also the machine's performance against factors like pricing options and operations.

'Companies can apply user feedback to help design improvements in upcoming versions,' said Aurin. 'You can identify which features are most important for users by location and which are not.'

Smarter Marketing and Sales

Machine learning also played a role in marketing and sales campaigns through SAP Marketing Cloud. For example, if customers shared negative feedback about a machine, the company could use that intelligence to target those groups for discounts to win them back or up-sell new coffee makers. Mobile alerts helped the sales team schedule on-site visits based on data indicating which customers are likeliest to take advantage of special offers. All the while, SAP Analytics Cloud continuously tracked sales forecasts and actual deals mapped to campaigns and lead opportunities.

Stay on Top of Coffee CommunityTrends

Social data is huge in the coffee industry. Aurin showed me how SAP solutions could help capture and share the latest drinking trends, from espresso snacks and supplements to fair trade and coffee cocktails. Once customers opted in through their mobile app, companies could securely track their social media posts to determine their interests over time. With chat bots in a mobile app, consumers could communicate their preferences and wish lists.

'Within SAP Commerce Cloud, companies can create more targeted personalized offerings,' said Aurin. 'Meantime, companies can see the trends from the anonymized data, and calculate expected revenue based on potential uptake.'

Even the packages of coffee beans in this prototype store held potential for a better experience. Consumers could scan the coffee bags with their mobile app, and the technology read the label to identify which brew best matched their tastes, based on their past coffee purchases and ratings.

During SAP CEO Bill McDermott's keynote at SAPPHIRE NOW, he talked about how companies need to close the $1.6 trillion gap between customer expectations and what they actually experience. This is the new experience economy that coffee drinkers are most energized about.

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