The consumer goods market is changing quickly—and digitally native brands are rapidly winning market share.
“If you want to survive, you need to invest in connecting and directly engaging with customers," said Salesforce's Sophie Verwater, speaking at Dreamforce 2018.
Businesses must learn to move quickly, testing and learning what works and what doesn't. Artificial Intelligence (AI) can help.
The new marketplace offers new opportunities to tap into AI to get ahead.
The pressure is on, but the shakeup in the marketplace also offers businesses an opportunity: Businesses that can collect and connect their data, making data the heart of their business, will be able to adapt and thrive in today's market.
If you want to survive, you need to invest in connecting and directly engaging with customers.
—Sophie Verwater, Salesforce
- connect their distribution channels for smarter planning and execution
- connect their operations so that their headquarters are linked with manufacturers and suppliers
- connect their employees to attract and retain top staff
- connect their customers to build brand loyalty
AI allows businesses to tap into that data to uncover trends and insights that they can then act on. For instance, a large beverage company used a mobile app and AI to photograph and audit grocery store shelves carrying its beverages. It could assess which products sold and needed to be replenished, coupling that data with, for instance, the weather, to predict the best sales opportunities.
AI can predict the best ways to promote consumer goods.
In another case, said Salesforce's Reinier van Leuken, AI could be used to help a business figure out how best to promote, say, their potato chips: When should the brand promote the chips? How long should the promotion run? Should the promotion run in grocery stores in the city or in the suburbs? During what kind of weather?
Businesses could use AI to examine past sales and past consumer buyer behavior across more than supermarkets and across the many flavors and brands of chips sold. It could see the average number of bags sold per week, per store, for a particular brand, comparing and analyzing that data against other factors such as weather and location. The AI program could then predict ways for the business to improve its promotions to sell more chips.
For Anheuser-Busch, implementing AI meant getting the team on board.
For Anheuser-Busch, AI has helped the company find ways to save costs, be more efficient and drive revenue tenfold, said Gabriel Gaspar, global director of innovation for Anheuser-Busch InBev. The company began by testing AI with one project, then building up to additional projects. The biggest challenge, said Gaspar, was engaging employees, developing internal knowledge and fine-tuning the process. “People need to understand why [the program] says what it is saying," Gaspar said.
It takes time. Anheuser-Busch is using AI to translate images into data: To get a 65 percent accuracy rate, Anheuser-Busch first had to feed more than 100,000 images into the program. But from there, the program has evolved quickly and grown.
Hard work comes first, said MARS.
For MARS, the challenge with AI was the work it took to get there. In superhero movies, says Amit Apte, digital foundations integration director for MARS, there is always a prequel. “How did the superhero get their power?" he said.
The answer for businesses using AI? It's all about the work the companies must do to unlock the data and make the data accessible so that the company can use AI to analyze it. The colorful sales charts, sales forecasts and market predictions—none of it is possible until a company figures out how to feed the data into the system.
But companies shouldn't treat the project as solely about AI.
Indeed, said Colin Gelfer, co-founder of Atrium, a Salesforce consulting partner, the most successful companies spend the time to “build the pipes" so that data can continue to be added and used.
The other challenge? Changing the company's mindset, Gelfer said. It's not so much an AI project as it simply is a way for a business to drive the outcome it wants. The business outcome—and not the technology—should fuel what the business is doing.