Joshua Dreller, Sr. Director, Content Marketing @ Skai
Joshua Dreller, Sr. Director, Content Marketing @ Skai
It goes without saying that one of the requirements to make the best data-driven decisions is to have great data.
CPG data analytics consists of consumer insights and predictions generated by analyzing predetermined data sets, contextualized and uncontextualized. The data could include things such as consumer behavior, sales trends, competitor analysis, fluctuating prices, distribution information, customer demographics, transaction information, purchase frequency and brand or store loyalty.
CPG companies use the data to spot short-term and long-term trends, and then organize the data in order to inform business decisions, such as new product launches.
While there are a wide array of CPG data analytics that could be useful, the key datasets that are currently being prioritized and sought by CPG marketers generally fall into three categories: retail analytics, marketing data, and customer insights.
This type of data tracks and monitors online retailers for your brand as well as your competitors and is important because CPG marketers must be able to react to the rapidly changing market. With the right retail analytics in place, practitioners can predict trends before they happen and act upon those insights to make successful and profitable decisions.
There’s also just monitoring the “digital shelf.” Oshiya Savur, Head of US Marketing and Education, Luxury Division at Revlon says that Revlon “spends a lot of time on channel conflict management, whether that’s managing inventory that has appeared from gray-market sellers, or managing the impact of price-matching between retailers during events like Prime Day.”
This chart appears in the Skai report, Mind the (Data) Gap: What CPGs need for retail-intelligent advertising and ecommerce success.
This type of data delves into performance insights derived from advertising practices. Part of the shifting media mix to digital channels is due to the need for CPG marketers to engage in performance advertising and not just the brand marketing with which they have historically been tasked. When armed with advertising analytics, CPG marketers can make informed decisions about how to allocate ad budgets, set efficient media bids, and optimize messaging to improve and maximize their Return on Investment (ROI).
“Effective use of digital requires the right trigger with the consumer to grab their attention and deliver the desired message. This requires an almost instant connection with the customer. As consumers become increasingly accustomed to personalized digital marketing, a stagnant banner ad or disruptive ad without context no longer suffices – digital marketing needs to be hitting the right person, at the right time, in response to an active need.” – The Evolving CPG Marketing Mix
This chart appears in the Skai report, Mind the (Data) Gap: What CPGs need for retail-intelligent advertising and ecommerce success.
This type of data helps CPG marketers understand the customer journey and better market to them across the funnel. In the recent Gaps in Customer Experience Harris Poll, “53% of consumers surveyed said that they expect a brand to know their buying habits and preferences and should be able to anticipate their needs. Further, 37% said they would stop doing business with a company that doesn’t offer a personalized experience…The fluid, omnichannel buying journey is here, and unless a brand shows a customer that it cares about them along every mile of a dynamic journey, the customer may have switched brands by the time that all-important last mile comes into play.”
The new expectations that consumers have for brands require not just a fundamental understanding of how and why consumers purchase, but a granular level of data down to the customer journey level in order to achieve. According to Nielsen, “Two critical issues that advertisers need to determine in executing their online advertising are which audiences to target and which sources of data to use to reach those audiences. There is a wide range of data sources available to define and identify audiences, which all come with different costs.
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