Customer loyalty is everything in the world of consumer-packaged goods (CPG). Products can fly off the shelves or sit unsold for months based on the needs and perceptions of a fickle audience. To keep ahead of the competition, many CPG companies have turned to a coordinated analytics strategy.
The stakes for CPG companies could not be higher. Industry sales in the United States alone are expected to grow to $721.8 billion in 2020 up from the $635.8 billion recorded in 2015, according to compiled data at Statista.com. Much of the growth comes from emerging market economies and the subsequent increase in global consumption.
One tactic in gaining market share and mind share is the use of analytics in customer clustering. More advanced than market segmentation, manufacturers and retailers cluster data into units with similar behaviors that may be managed together to predict desired outcomes.
To help make sense of the impact of data analytics on the CPG industry, we invited Ashish Joshi—senior director of data, analytics and data science at The Clorox Company—to our Analytics Advantage podcast. A 17-year veteran of Clorox, Joshi leads a team of data management experts, advanced analytics professionals, and data scientists spread across business divisions and centers of excellence. These teams work on different analytics focus areas like business performance tracking and forecasting, advertising, trade promotions, market structures, and marketing personalization.
"The retail landscape is changing, and ecommerce is putting a tremendous amount of pressure on retailers, leading to greater emphasis on private label and that drives pressure on brand manufacturers like Clorox," Joshi says. "Everyone is in a battle for consumer insights. So, we must get smarter and faster in generating those insights. We communicate this to our retailers make sure we keep the overall value front and center as we are building our products and creating our advertising. That's where our analytics comes in."
Like Clorox, consumer goods companies rely on a limited amount of available transactional data. Manufacturers might know where and when an item was sold and for how much, but nuanced data such as what else might have been in the shopping cart at the time of purchase could lead to deeper insight and brand loyalty.
"We have a lot of data about our consumer that can be used to create consumer clusters," Joshi says. "We are not to a point where we are personalizing to a specific person but we are personalizing to groups of consumers. The number of groups of consumers that we talk to is growing."
In the last three years, Joshi and his data science team have poured over the consumer segments with analytics tools to find out more about how these consumer clusters can be created in a way that can drive the effectiveness of our interactions with the consumers. This is similar to the age-old market segmentation, just order of magnitude more granular.
"We have done segmentation for so many years," Joshi says. "This has resulted in five or six consumer clusters. With the amount of data that is available now, we have our data science team identifying many more different clusters and that can help us serve our consumers better."
Joshi says another key to his team's success is using analytics to see how dynamically the attributes are changing. "Analytics helps us identify those different consumer attributes that really matter," Joshi says. "I could come up with 10,000 attributes, but I have to focus on the ones that are really important so we can supply customers with the right offers and communications."
Often, CPG companies will use promotions to gauge how individual products are performing. These often use trade analytics that looks at trade promotion programs. By working with sales teams and retailers, the analytics helps companies determine how and where the promotions are working and potentially how to optimize them in the future.
"Pricing works off of fundamental measurement of the impact of our pricing and promotions. Joshi says. "Some of the pricing that we do is more tactical, but we are also involved with strategic pricing where we look at our three-year plans, we look at our products, we look at the markets, and we look at our competitive positions. From that we make recommendations and we look at what types of activities can be put in place to keep pricing low."
Building the right data pipelines is critical to companies like Clorox for measuring and analyzing marketing optimization and effectiveness.
"You can look at specific brands and see how much they are spending on streaming videos versus banners versus television and optimizing the overall video spend," Joshi says.
To hear more about Clorox and customer clustering, check out the entire conversation on the Oracle Analytics Podcast (click the icon below to listen on our Oracle podcast player):
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