2020 saw the highest growth in grocery retail in 26 years. Simultaneously, the biggest ever jump in ecommerce saw 1 in 5 households ordering groceries online, and a 75% y-o-y increase in September 2020 (Kantar). This essentially equates to an advancement of 8-10 years vs the pre-pandemic ecommerce trend.
As described by Matt from tcc, shopper behaviours have changed considerably. Not only in the use of ecommerce, but with big swings back to the weekly ‘big shop’ at a superstore and significant increases and decreases in demand for some categories.
For Alaric at Heineken, 2020 brought about supply challenges as beer and cider consumption shifted to the off-trade, with questions of demand generation replaced by how best to service one sales channel. Focus turned to cost management, reshaping budgets and logistical problems.
Similarly, Peter from Morrisons described a significant increase in pace for an already fast-paced environment, with the whole supply chain needing to come together to feed the nation. Everything had to be driven by avoiding disruption to the supply chain.
Looking forward into 2021, the pace has continued as has the laser-sharp customer focus, where data can be used more than ever to prioritise resource and effort according to what brings the most benefit in the shortest time. At Heineken, 2021 is likely to be a year of two halves; serving the off-trade and dealing with the uncertainty of recovery will be followed by portfolio refinement to address range rationalisation.
Loyalty will be a priority, with brands needing to figure out how to keep the shoppers they want and win back those they lost. Factors such as shopper austerity and economic uncertainty will make price a more important driver. With it comes increased shopper promiscuity and the big supermarkets may once again lose out to discounters. Movements to support local suppliers, community, home cooking and sustainability will come to the fore.
All of which raises some significant challenges and questions for the sector.
While it is unrealistic to expect to maintain this level of growth, investors will be keen to see brands capitalizing on it. Their task will be to understand how to drive shopper loyalty and revenue growth. With the shift to ecommerce, the challenges are less about proximity to the nearest retailer and more about user experience, including the availability of delivery slots and quality of service, such as delivering exactly what was added to the basket.
Data science has a huge role to play in delivery optimisation and fulfilment mechanics, such as informing real estate decisions about how, why, where and when to locate and use dark stores vs picking from the store network.
The trend towards range rationalisation has been reinforced through an increase in private label adoption. This raises the key question of how brands are able adequately to differentiate in each category to continue to compete.
As the ecommerce user experience continues to evolve, assortment optimization can help to bridge the gap between browsing online and the store experience, with data science helping you to understand how to drive and measure brand distinctiveness and achieve sustainable brand growth.
While an increased need for agility was forced upon us, there have been some positive changes to ways of working to be more agile in future. Retaining this both attitudinally and operationally will be important, moving away from static brand planning to a more fluid approach. Techniques such as multi-KPI scenario planning with the right leading indicators can guide the decisions about where the greatest opportunities exist within an overall budget.
For data science teams, the trick now is to balance responsiveness to the increased demand of the data science team with the time needed to allow the data scientists to think and do their best work.
Businesses that are managed in silos, often by necessity and driven by different skillsets, can miss synergies and interactions across functions, platforms and data sources, especially where there is no shared language of performance, poor accessibility and a lack of understanding of critical information. As Alaric described, different tech stacks, data ecosystems and lack of integration makes scaling advanced analytics difficult, however, the advancements in cloud computing offer greater opportunity for scaling, unification and the mass adoption of data science.
Gaining senior leadership buy-in to address issues of inter-team collaboration, platform and data silos, as well as getting the right people upskilled and able to hypothesise and ask and the right questions, was universally echoed across the panel.
The panel also agreed that it is critical to make data science readily accessible to those making the business decisions, especially if you’re to be successful in creating a culture of data-driven decisions. At Ekimetrics, we have the “Three Us” mantra – Useful, Usable, Used to drive the adoption of data science throughout an organization.
Where the last 5-10 years have been about building and refining data lakes and models, the “next frontier for where we go as data science leaders” is to embed this to be an enabler in the operation.
Data Science cannot be only for mathematicians and computer scientists, as Peter has been discovering during his first 18 months at Morrisons. Finding unexplored talent from within the business and bringing everyone together in the right kind of culture, with broader skillsets, such as how to ask the right question to get underneath difficult problems and deep business knowledge, has brought better opportunities to translate the impact of the algorithms into something the business can see.
Business knowledge and the ability to translate between business and data science is critical to the success of data science projects. Just as building teams that have strengths in managing stakeholders is critical to demonstrating the value of data science to senior leadership.
The events of 2020 have changed habits and broken models.
Understanding shopper trends and behaviour and being responsive to them in the right way will be critical to driving loyalty and profitability over time. As Matt from tcc pointed out, the retailers that will be the most successful will be those that bring loyalty into their whole business and embed their way of being with customers, rather than regarding loyalty as isolated communications exercises. Balancing both transactional and emotional needs will be key.
The shift to ecommerce brings its challenges, such as losing opportunities for spontaneous purchases. However, there is opportunity to get highly targeted offers in front of customers, which in turn gives a greater opportunity to serve customers better.
A core challenge, as described by Alaric, will be asking ourselves which behaviour changes are a long term shift and which were forced by closure of parts of the economy. The models we had pre-Covid no longer work and they will change again. As Peter put it, we have to expect the unexpected. Contingency planning is an essential part of business.
Ultimately, stronger data analytics cultures will help brands to take a longer-term view, identifying and understanding where the biggest impact can come from, and the role of data science will adapt to be a more integral part of the most successful businesses.
Watch the recording here:
You can also join us at 10:30 on 4th March to hear Matt with special guest, James Wheatcroft, VP Marketing Northern Europe, Accor, at an exclusive ISBA event, discussing how multi-scenario and leading indicator analysis can help brands move their marketing planning through and ‘Beyond Uncertainty’. You can also join them at our Festival of Marketing short at 14:15 on 22nd March.Download our latest Grocery report