Once classed the pillars of our high-streets, department stores are now facing troubled times. They’ve developed a reputation for being outdated, as customers have opted to shop online. Experts describe department stores as lagging, claiming some “haven’t changed in 10, maybe 20 years”.
With House of Fraser closing half its stores, and John Lewis’s plummeting profits, it looks like department stores’ heyday is behind them. These former retail giants seem slow to adapt to the newest trends and failing to close the digital gap, featuring lacklustre websites or offering poor online experiences. Clearly, they are under pressure to adapt in order to survive and stand a chance of winning the retail war.
Many of today’s ailing department stores are trying to navigate the gap between profit margins and investing in their customer experience. The retail landscape has shifted from product-centric and purely transactional relationships, towards customer-centric experiential shopping, and customers increasingly want to feel that brands understand their lifestyle and help them live it. Brands, including department stores, must now exhibit emotional intelligence to stay relevant.
We are in the age of the customer: consumers are empowered and have expectations as to how, where and when they wish to be engaged. Customers have many channels available to them, and are increasingly looking for a single, unified brand experience.
But how is this displayed? How can department stores (and other retailers) enrich their customer experience through their marketing strategies?
One way is to capture data from multiple channels to gain a true 360° single customer view. This data can then be translated into actionable insights to orchestrate individualised customer relationships across multiple channels to deliver the right message at the right time, using the customer’s preferred channel.
Given the criticism on the poor online experience department stores’ websites receive, they need to create tailored experiences which will resonate with customers using transactional, behavioural, and demographic data sets in real time.
With data-driven marketing, retailers can adopt an experimental approach: Creating dynamic micro-segments based on behavioural data, conducting test/control and ABN testing to selected micro-segments and then adjusting strategy based on customer response and financial uplifts.
Marketers are increasingly turning to machine learning and AI to customize and personalize at scale. In particular, predictive behaviour modelling allows retailers to be able to anticipate the future behaviour of customers based on advanced data insights, and self-optimizing campaigns set to deliver the most effective communication to every customer at any given time.
By adding in data science, retailers can ensure their communication resonates with individual customers, leading to greater satisfaction and brand loyalty.
Optimove is hosting the annual Optimove Connect conference in Tel Aviv. This premier event brings over 900 strategists, brands and thought leaders from around the world to discuss the art and science of relationship marketing.
By Roni Cohen, director of data science at relationship marketing experts Optimove.