matt

Matt Holland
Head of CPG Enterprise AI at Hypersonix, Inc.

LinkedIn

Polite smiles, nodding heads, and … an innate belief that it’s just too good to be true. 

We understand why that is a common response from CPG business executives listening to vendor pitches. After all, Gartner reported back as early as 2017 that roughly 85% of big data projects fail and that, through 2022, only one-fifth of analytic insights will deliver business outcomes

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Hundreds of vendors are out there pounding the pavement for a share of the rapidly growing data-based analytics business with the majority overpromising and under delivering. 

As a CPG company vying for customers who are browsing and shopping an ever-expanding list of physical and online channels, you want to make sure you select the solutions that will make the best use of your limited IT dollars. You want to prioritize technological implementations for your limited technical staff that will actually generate a return on investment for your business. 

The Interaction Between Brand and Analytics 

It’s important to define major challenges at a CPG before looking at possible solutions. By clearly understanding pain points, it will be more obvious whether a given solution generates a return on investment. 

For example, many CPG companies may require five or more days to obtain the answer to a typical data analytics question. Let’s say a product manager is wondering why Midwest sales are down. She meets with a data analytics professional who then returns to his office to run multiple queries against internal data. During this process, he solicits input from a vendor and determines that it’s too cost prohibitive to obtain outside assistance. Instead, the data analytics professional does the best he can do on his own and creates reports, dashboards and slide decks. He sends an answer to the product manager a week later.

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In the meantime, the product manager recalls a promotional campaign that boosted sales the previous year in that Midwest store. She decides that the reports are taking too long and instinctively approves the same campaign in an effort to improve her quarterly numbers before too much more time passes. 

However, when the data analytics reports come back, the queries show that Midwest sales are down because of weather-related issues that occurred the previous month. The best solution, according to the analytics report, would be to shift product offerings to address different consumer demand — not to launch a promotional campaign for current items. 

The product manager then must shift gears, decide whether to continue with the current promotion or initiate a major product shift instead. In addition, she realizes that she didn’t take into account the recent launch of a sister ecommerce site when she outlined the parameters for the data analyst professional, leading to possible inaccuracies in the final analytics report. 

Accelerating Analytics Now Necessary 

Over time, this sort of brand and analytics interaction grows more and more inaccurate. It’s easy to see that many factors can affect the answers to why something is happening in the CPG world, and what’s more, those factors are constantly changing and shifting — often while professionals are trying to find the answers. 

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Today, new tools based on artificial intelligence (AI) and machine learning (ML) are within easy reach of CPG business professionals. In essence, these AI and ML solutions accelerate the speed with which data analytics can occur. With the right application, the technology is available to provide data-based answers right now — not five to seven days down the road. Those CPG companies who embrace these tools will have a clear competitive advantage and be able to accelerate their growth in unprecedented ways. 

The Hypersonix Advantage

What makes Hypersonix different?  

The three main ways that Hypersonix accelerates this data-analytics speed is by unifying your existing data to create a better foundation for analytics, by adding business intelligence using a natural-language Google-like interface and by creating a seamless user experience that can allow non-technical users to create their own dashboards or run advanced modeling updates and provide an immediate and actionable answer. 

For example, once disparate data sources are unified for a CPG business, our product manager can ask her questions about why Midwest sales are down while she’s sitting in a meeting with her team. Hypersonix provides both a personal assistant named Jarvix and a Google-like interface, both of which use ML to answer the question immediately. 

The team can then discuss the answers, alter follow-up questions, and make additional queries to Hypersonix, which continues to analyze and review that unified data set to provide more immediate answers. By providing real-time intelligence and advanced analytics, Hypersonix gives that CPG team all the information it needs to make data-based decisions and come up with actionable items by the end of the meeting. 

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See for Yourself

Does it still sound too good to be true? Contact our team for a live demo of the Hypersonix product, which uses actual data to illustrate how the solution delivers what we promise. We also work with our clients to build a pilot project first, with a limited amount of data and targeted application of our AI and ML tools, so you can generate real results before making a major commitment.