Solving the Physical/Digital Riddle

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Solving the Physical/Digital Riddle

05/12/2017

Chris Morley has spent more than two decades in the retail and consumer goods industry and worked on three different continents. Last year the CPG veteran arrived stateside to serve as President, U.S. Buy, for Nielsen, leading an organization that helps clients drive growth through a deeper understanding of shopper behavior. Morley spoke with Retail Leader about global trends, changes in the U.S. landscape and how Nielsen is helping clients make sense of it all.

Retail Leader: You've been in your current role for about a year, but it was quite a journey with Nielsen before that, including stops in Australia, Vietnam, China and then western Europe. What are your thoughts on the U.S. market now that you've been immersed for a while.

Chris Morley: The U.S. is recognized, and deservedly so, for having one of the most developed and fastest moving of the consumer packaged goods industries. But the pace at which things are changing has accelerated and is being led by the consumer who lives in a very omnichannel environment. They consume media differently and they shop differently, which creates challenges for how the marketplace is measured. There are also many more opportunities to understand the consumer because more data and analytics are available than ever before. As exciting as it is, it is also more challenging for our clients, retailers and suppliers to make decisions.

RL: There's more to measure but it's more challenging to measure?

CM: In an omnichannel environment combined with the growth and entry of discounters actually measuring what's happened in the marketplace becomes increasingly important and arguably more difficult as the industries fragment or there are more channels and more options. This is occurring alongside the need to keep pace with providing more granular analytics to help understand the change that has happened, what decisions should be made. We are measuring that fragmentation and providing our clients with better tools to decide what to do next.

RL: A lot of change is coming in the food retailing world judging from the research Nielsen and FMI (Food Marketing Institute) released earlier this year. The research projects that food sales will reach $100 billion by 2025. Is the pace of change happening so fast that that number needs updating already?

CM: It is too soon to revise that number, but it is important for us to illustrate just how large and impactful we expect this change to be even though it is difficult to forecast that far out with precision. The work we did with FMI was necessary, to listen to consumers, look at the trends and put a stake in the ground about the size of the opportunity. I think that forecast, which is part of a multi-year project, is probably a lot bigger than other commentators had come out with previously.

RL: Either way, the industry is in for a huge shift, which underscores some of the challenges you described around measurement and gleaning actionable insights from new data sources.

CM: Two big points to your question. The first is the growing role that everyday analytics will play in how companies navigate the shifting landscape. Our clients have always valued advanced analytics to guide their annual strategic planning, but, true to the times – actionable insights on a daily basis is what's needed to keep up with the constantly changing, daily conditions of today's fragmented marketplace. The second big piece is e-commerce. We have started to release our e-commerce measurements in the U.S. There's probably six or seven markets across the world where we think it's most important to have that measurement up and running as soon as possible. The U.S. is one of them. We are gradually releasing category level detail throughout 2017, which gives us the ability to zoom into certain categories or segments of the shopping experience and look at different growth rates.

RL: What are you seeing so far?

CM: If you take what we define as grocery and all of the categories that go into food and beverage, around 20% of the growth overall in 2016 is from products sold online. Now a lot of the products in food and beverage are those in the perimeter of the store, and fresh items and stuff like that. Those categories that are less developed online. So when you start to look at others, you see much more impressive growth rates coming from e-commerce. For example, in household products, more than 40 percent of the growth of those categories is attributable to e-commerce, compared to 50 percent in personal care and nearly 80 percent in pet care.

RL: Those are substantial contributions coming from e-commerce even if the overall business is growing slowly.

CM: The total growth rate for grocery last year was about 2 percent with about 1.5 percent of that coming from brick and mortar. In center store categories, those that we predicted or said would be influenced by e-commerce, we are already starting to see large proportions of overall growth coming from e-commerce based on the early reads that we are getting from our online measurement.

RL: If center store business is migrating online, that presumably gives retailers an opportunity to redeploy space. Are you seeing that?

CM: Understanding what the assortment should be in-store versus what it should be on the e-commerce platform has becomes increasingly important. There will be pressure on the space which is why it is so important to have a deeper omnichannel understanding of assortment and pricing decisions. For example, we are doing a lot of work to help retailers and brands understand health and wellness trends to determine assortment and on pack messaging to customers and how that is shared in an online environment.

RL: Is that where your relationship with Label Insight comes in?

CM: Yes, In today's consumption climate, there is an appetite to gain a more in depth understanding into what ingredients and nutrients products contain, beyond the marketing claims on the packaging. Nielsen's robust market measurement and Homescan Consumer Panel data are combined with Label Insight's cloud-based product attributes. Together this brings an unmatched level of data granularity to food manufacturers and retailers, designed to transform on-pack nutrient and food ingredient labels into quantifiable attribute. Traditionally Nielsen would have coded and collected information about a product by taking a photograph of the pack and coding everything that was on there, plus the physical attributes. What we are doing with Label Insight is taking the ingredient list as well as the information and trying to decode that at a very granular level. Different colorants, different ingredients may be called many different things. And there may be a number of things in the store that fit a health and wellness profile but maybe don't say that on the pack. And so we are able to code all of those attributes in a very consistent manner.

RL: Many retailers are in uncharted territory now. Whether it's how to deploy stores, doing more with digital. When you talk to clients, what are the one or two problems they are asking you to help them solve most often?

CM: The number on thing is how to fully decode and understand the marketplace in a broader perspective and understand how e-commerce interacts with brick and mortar.

RL: Revisiting the $100 billion figure from the Nielsen and FMI study, even with better measurement, doesn't it become harder to attribute a sale to a specific channel?

CM: It becomes more difficult because there's an enormous amount of data and expertise in that area to stitch together. There's consumer-based measurements with traditional POS data or consumer panels that enable you to track what's happening, although when you do that approach you don't necessarily get the granularity and accuracy. We have the capability now to use person-level data sets to connect someone's media consumption and other behaviors to their spend activity. And while that may not be totally representative of the entire industry, it's extremely granular and enables almost real time decision making.

RL: Explain what that means please.

CM: By reducing the time, cost and resource demands of traditional analytics, coupled with simple and intuitive tools, our Everyday Analytics will make sophisticated analytics more accessible for everyday decisions across all FMCG growth drivers, including price and promotion, advertising and innovation. To explain this further, traditionally you would run a marketing mix model using store data and it could take a month or two to be able to understand all the different drivers of the marketing mix. We are now able to do that almost in real time and refresh the model every time the data refreshes. That person level data allows you to understand consumer behavior. The secret sauce is often how you connect these data sets on a person level.

RL: The notion of big data not being better data is interesting. What are your thoughts on AI and machine learning, two of the hottest topics in retail right now?

CM: Clearly AI, machine learning are important. They are buzzwords to the extent that you could argue the word AI is often used when perhaps machine learning should be, in terms of whether something is artificial intelligence or just a clever algorithm. Just to give an example, the coding of these millions of items from e-commerce, consumer captured receipts, is not something that can be done manually. So you need to have machines that learn how to code those products.