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So there’s this concept called the zero moment of truth that Google has coined, and it’s a derivative of a Proctor and Gamble concept called the first moment of truth where a consumer will at the shelf decide at that point to buy the product. What’s happening is that consumer behavior, because of mobility and social media, that the shopping experience has actually spanning both the out of store experience, on the go at home, into the store.
It’s really creating this mandate I think for consumer goods marketers to really understand consumer behavior and use that to inform both the strategy and the actions of their marketing in a way that the former model of doing one off promotions and campaigns doesn’t fit well with. And this presents an opportunity for BI vendors like InetSoft to help them from a number of perspectives, both on the data and analytics side, but also on the action and marketing automation side.
There are three different areas where the consumer goods industry needs big data analytics. There’s the consumer side of things which is what I just described. There’s the retail channel side. CBG companies spend a lot of money with their retail partners to conduct trade promotions and shopper marketing programs to help drive demand in the store environment, and so we focus there as well.
And there’s a number of interesting things that happen there, but the first is visibility into all those different retail relationships by getting point of sale data and building a data repository and using that to inform a number of activities from how you allocate the marketing spend to just what’s working, and avoid what’s not working. Increasingly they are trying to relate that data to the consumer marketing action as well because millions and millions of dollars get spent across those two areas.
The third area is, of course, operations. So traditional supply chain oversight and that sort of thing, people use our BI software there help analyze data and make sure that as much as possible that consumer good companies can implement a demand driven supply chain so that out of stocks on the shelf don’t happen. At the end of the day, there’s a dashboarding and analytical platform that can span all these different areas with a goal of better serving the customer, which in turn translates into better corporate performance.
Speaking of large data sets and data complexity, there are new challenges that CPG companies are facing. Social media is very hot topic right now, and marketers in every industry want to understand how to tap into that. There’s a number of ways in the CPG space that this is possible. Social media is a significant source of big data.
It’s not just Facebook or Twitter, but it’s all the attributes and all the actions of people who follow your brand that become significant actions you want to understand and capture, and that’s not a steady state. It’s a growing and a dynamic sort of data source, and that implies, itself, that it’s a big data problem as you expand beyond social media to just digital channels in general.
The entire global Web from blogs to Web sites to magazines that are online to reviews of products to comments that get posted to articles, the smart CPG companies will implement solutions that will capture all these things and can help really inform the types of products they develop, the messaging around those products, the products they launch in the marketplace, and the promotions they conduct.
They are using consumer insights to really drive the next best action tactics: coupons, offers, and incentives. They conduct life stage marketing so that as people transition from different phases in their lives that you match up your products. That’s really important with multi-brand CPG companies where it’s, of course, the brand manager’s responsibility to sell as much of their product within their particular area, but then the overall brand, itself, they want to optimize the consumer relationships across those brands.
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And that creates a number of issues as well. In the retail channel harmonizing the data sources from all the different retailers is complex. That’s a big data challenge. That’s also very dynamic and changing as well. And so taking all this together, this environment does create a lot of big data problems. We believe we have very nice solutions that address both the data complexity challenges and the unified analytics challenges.
The goal is to connect the insight to action throughout the marketing organization. CMO’s are under very much pressure. Their tenures tend to be less than their C-level peers, and so when we approach them, it’s important they understand that we understand we have to prove value very soon, in the near term. Being very action oriented with analytics helps them improve sales quickly, and that’s really what they’re increasingly expected to do.