Where Should Consumer Goods Companies Invest: Product or Consumer Data
Social Media is now a key part of Consumer Goods’ Companies (CG) marketing strategies. For some years now it has been touted as a vehicle for CG to connect directly with end consumers to build direct relationships, and hence increase brand loyalty. In 2015 both The Economist and the Harvard Business Review heralded the ever expanding Internet of Things (through ‘Smart and Connected Products’) as the means to build these relationships. To build consumer relationship through both social media and IoT strategies requires the analysis of vast quantities of data. Any meaningful relationship with a consumer will also require clear identification of unique consumers, products and the many relationships between them. Assuming that there is a finite budget for investment in data and analytics – what data capabilities should a CG Company focus on for the best returns in terms of increasing sales?
At Informatica we have a sense of where the current focus is, which is based on the conversations we are having with a number of CG companies. However, I feel that our conversations are probably limited by the market’s perception of what we can provide, so I am not getting a complete view of investment options and what is driving decisions in terms of developing consumer relationships. I have set out get a feel for current investment trends based on a broader set of projects than we are exposed to at Informatica by leveraging Informatica’s excellent partner community. My plan is to share the results on my blog, and keep score of where a number of our partners would advise their customers to invest their marketing budgets.
To start the ball rolling, I have had a very interesting conversation with Devashis Senapati, Head RCG Benelux at Cognizant.
Immediately Dev came out in support of an investment in product data as a high priority, but perhaps not in a way that is expected by a market which has been saturated with big data hype for so many years. Dev is seeing that it’s not yet about the big data (how people interact with a brand or product. Instead, current efforts are about what I call the ‘little data’ – that is the data about the product.
“The data about the product, and how the product differentiates itself is the most important. This is how a consumer will be convinced to buy one brand over another, even justifying a higher price point.”
This makes sense. According to Cognizant’s European Shopper Study Reports 2015/16, the amount of research consumers are doing on the internet before going to the store to make a purchase has been increasing. In all the surveyed Markets (Benelux, Nordics, UK and Germany) consumers do a significant amount of research of the products online before making a purchase. Separately, the 2015 Marketing Sherpa Consumer Preference Survey showed that 59% of shoppers still discover products in store, so all channels remain important. But as Informatica’s Ben Rund notes – even stores are becoming more digital. The message here is clear: If your product information is not available across the increasing number of digital channels, your product has a high probability of not being considered in a purchasing decision. In today’s information-driven society, this means more than just a product name and item number. Clear, high quality photos and in-depth product details should be posted across all digital channels, both the CG corporate websites – with links from social media microspots – and retail partners’ websites. Print media has also not gone away yet, so instead of consolidating the number of channels through with a CG company can reach a consumer, it is increasing.
But what of the big data aspect that the media is focusing on: consumer sentiment, product behavior and product usage data? Dev sees a very clear role for this data: “CG companies need to know why people are buying their product, how are they using it and what features are the most important. This varies by market. So they need to understand how to market this, what product features to highlight in each market to ensure their products are as attractive as possible”.
So again it is coming back to the little data: data about the product. Dev clearly sees that all this analysis should support the ultimate goal of the company – to sell more products. Analysis should underpin both innovation and product positioning, rather than be analysis for analysis’ sake. “Too much analytics is also not valuable – it needs to be focused.” I agree, and would go a step further – it needs to be usable. In the context of consumer experience management this means influencing which product data is highlighted to which consumers in which markets across a multitude of different channels as they make their buying decisions.
Consumer data clearly has a part to play in the understanding of why consumers purchase different products. Dev notes that CG companies have been making inroads in terms of building brand loyalty via social media channels. However, not many companies have succeeded in building a single view of an end consumer across all departments and brands. This is due to a number of reasons, including the extensive use of marketing agencies in some regions, and the fact that in all regions the retailer still owns the primary transaction with the consumer, and hence the primary relationship (and more complete set of data). Some CPG companies/brands that are large enough and/or focused enough (e.g. Nespresso, Nike) are taking it further and opening their own stores. In these direct-to-consumer scenarios, the CG company will be able to build a more complete picture of consumers, and hence a closer (and more measurable) relationship that those that are limited to social media for consumer interaction.
Another consideration is, that unlike product data, which a CG company has direct control over, consumer data is a resource that they may have some access to. Outside of the direct-to-consumer scenario, consumer data can’t be considered complete or reliable. It is far easier, and more repeatable to deliver value from managing a set of data that is complete, and that you own.
In summary, consumer data, and big data analytics will play an important supporting role in delivering insight as to why consumers choose your products.
I feel Dev justified the investment in distributing high quality product data across multiple channels as a key investment area very well. Ultimately it is the wide availability of relevant product data that will more directly influence the key CG goal: Sell more products!
So – back to the original question: Which data capabilities should CG companies prioritize?
The score to date: