With the overwhelming amount of data available, Stephanie Augier, European lead for analytics at IRI, discusses the importance of analysing Big Data to unlock its full potential.
As store shelves become increasingly full of products, retailers, manufacturers, brands and their supply chains are facing major challenges in a bid to put the best and most profitable products on supermarket shelves – but not necessarily the most products.
Today the focus is on what categories and products can provide them with the most incremental growth, but which can also satisfy the retailer’s need to improve category performance overall.
Every manufacturer, for example, needs to look at what is unique about their product or brands from a shopper’s perspective. Every product must have some level of uniqueness, so that shoppers can then decide which brand to buy over another one.
If an organisation wants to enhance its product offering in a category, it needs to offer more than just the basics. In a category that is largely dominated by retailer’s private label, such as ready meals, Prosecco or milk for example, brands need genuine differentiation, not just to survive, but also to drive shoppers to come to the point of sale because they know they will find a product with the attributes they want more than anything else.
In a busy category, which may have an overwhelming array of choices for the shopper, what makes them chose one variety and not another? What product characteristics are the most relevant for the different shopper segments coming to this banner in this market? What drives them to the point of purchase?
FMCG manufacturers and retailers are bombarded with data all of the time from so many different sources – from sales and store data to CRM and customer loyalty information, as well as an array of shopper marketing and digital media information – giving them an opportunity to look at every detail of individual customer preferences and shopper choices.
Unfortunately, having access to all of this data does not necessarily lead to better decision making. In fact, many retailers and manufacturers are struggling to cope with the mountains of data they have and making sense of it all, especially given that much of this information is siloed within individual departments, regions or markets. At the end of the day, they need to ask whether their data is working hard enough for them?
The untapped potential of big data is huge, and for manufacturers and retailers, being able to extract the data they need and then analyse it effectively will become more important for new product development and innovation, and for the development of effective pricing and promotional strategies.
In fact, product innovation is a key driver in helping achieve growth and profitability, and food manufacturers, in particular, could lose out on additional growth opportunities if they do not introduce a new product at the right time at the right point of sale, and within the right categories and/or universe, according to what drives the shopper to that particular banner.
Using predictive analytics, organisations can analyse key attributes of their products, including size, packaging, brand and pricing, alongside key competitor analysis, to help pinpoint what is likely to sell in different regions, store formats and so on. They can then work out how incremental a product will be before taking it to market.
Manufacturers also need access to powerful smart data – the combination of big data and analytics – to help strengthen the impact and return on investment (ROI) of their pricing, promotional and media campaigns (shopper marketing, advertising, mobile, social). This means knowing what is the right price point for a product, as well as being able to create and deliver the most effective promotional and media strategies, based on better forecasting and analysis of customers’ individual buying preferences and shopping habits.
With marketing budgets increasingly impacted by squeezing margins, due to flat FMCG market trends in many economies still, fully optimising investments is the key to growth.
Smart data and the use of analytics has become a game changer for the food manufacturers and retailers who chose to embrace it – from forecasting demand for individual products in different markets and even different stores, to optimising pricing and promotions in order to gain competitive advantage.
Many manufacturers and retailers have already established price and promotion optimisation as standard and as part of a growth management process, running ongoing models across all categories and products, and adjusting their marketing activity accordingly. This is typically supported by the whole business and often led by the finance teams who recognise the real value of smart data and analytics capabilities.
However, it seems that most have only scratched the surface of what is possible in this field and the opportunities that it can truly deliver.
