Supermarket shelves are become increasingly full of products, and as a result, retailers, manufacturers 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. Increasingly, 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.
Every manufacturer, for example, needs to look at what is unique about their product or products from a shopper perspective. It is clear that every product must have some level of uniqueness, so shoppers can then decide which brand to buy over another.
If a company 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 – ready meals 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?
Food manufacturers and retailers in particular are bombarded with data all the time from a variety of sources – from sales data to CRM and customer loyalty information, giving them the opportunity to look at every detail of consumer preferences and shopper choices. Unfortunately, having access to large amounts of data does not necessarily lead to better decision-making. In fact, many organisations struggle to cope with the data they have already and making sense of it.
Ultimately, they need to ask whether their data is working hard enough for them?
The untapped potential of big data is huge, and for both manufacturers and retailers, being able to extract data and analyse it effectively will become more important for future new product development, and for the development of effective pricing and promotional strategies. Product innovation is a key driver in helping achieve growth and profitability, and food manufacturers 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, these companies can analyse key attributes of their products, including things like size, packaging, brand and pricing, alongside key competitor analysis, to help pinpoint what is likely to sell in different geographies, retail formats and stores. 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 (advertising, mobile, social etc). 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 real game changer for 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 across various countries in Europe (and we are not just talking about the big ones) 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. 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.
