As the restrictions begin to ease, the retail industry should leverage analytics to tap into customer data and loyalty programs to cater to changing buying patterns
The three R’s — Restart, Revive and Reinvent — will be vital in retaining customers’ loyalty in the emerging new normal
Companies will have to re-imagine their digital experiences and leverage artificial intelligence to make customers feel valued
The COVID-19 outbreak has put every consumer back at the bottom of Maslow’s pyramid — ‘must-haves’ such as food and essential household items outweigh ‘nice to have’ items such as sports equipment, new cars and holidays. Yet, each of these businesses have loyal customers, who, if engaged properly, will help them survive the current crisis and be the foundation for growth in the new normal.
Retailers with rich customer data and loyalty programs have a distinct advantage here. But bombarding customers with ill-timed discounts and offers will simply not work. The current situation demands a complete repositioning of loyalty programs, leveraging both behavioral and emotional drivers. Emotion is one of the strongest drivers of retention, enrichment and advocacy. Making customers feel valued, appreciated and confident has a clear and strong impact on their loyalty.
In my opinion, as lock-downs and restrictions ease, and measures are taken to kick-start the economy, retailers will need to look at the three R’s — Restart, Revive and Reinvent — to retain customer loyalty. I will be exploring the three R’s in this article along the following lines:
Restart: How can you use your customer database to Restart your business?
Revive: How can you engage with your customers to Revive your business?
Reinvent: What are your customers telling you that will help you Reinvent your business?
All of these are relevant in one way or another to every retailer. For instance, for a grocery retailer, who has done well during the crisis, it would mean knowing how to keep customers engaged when the crisis is behind us. For non-food retailers, who are fortunate enough to survive the pandemic, it would mean understanding how to engage with customers to restart and revive their business.
Let’s examine the first R in detail.
As countries start to ease restrictions, customers’ buying behaviors have changed in terms of what they buy, sales channel, volume and frequency, and when they shop. The pandemic has turned consumer behavior on its head — previous consumer behavioral segments are no longer valid and new ones are fluid.
The first way to restart your business is to re-examine and re-define your consumer segments. For example, a typical family of four, whose parents used to buy dinner at the grocery store nearly every weekday on their way home from work, are now working from home. Due to the longer queues at the store because of social distancing, they now shop less frequently than before, their basket size is bigger and filled with a wider selection of fresh products focused on healthy eating as the parents juggle making dinner at home with their work and home schooling.
Let me share a real-life example. One grocery retailer saw a large uplift in sales within its fresh food categories during the crisis. However, what it didn’t recognize is that the new shoppers were coming from restaurants nearby which were closed due to the lock-down. Once the restaurants began offering take-aways, the sale of fresh food at the grocery store dipped. If the retailer had identified these new trends early on using its customer data, it could have started its own take-away counter and had opportunities to make customers try out its new offerings. Customer analytics would have enabled the retailer to solidify repeat purchases by better understanding consumer demand and building a more appropriate product assortment. This is certainly a huge opportunity that the retailer missed as the customer data was readily available.
Before I delve into the second R, I would like to highlight the example of retail giant Macy’s efforts to reopen all its stores across the U.S. shortly.1 The retailer is creating what is now termed ‘a socially distanced shopping experience’ to attract customers back into its stores. Measures include plexiglass barriers at cash registers, hand sanitizer stations, ‘no touch’ beauty consultations, cards sprayed with perfumes and colognes (to be handed over only if a customer wants it), and new rules for clothes that are returned. The company’s plans include having curb-side pick-up similar to that of Walmart. All employees will be required to wear masks and some will be required to wear gloves.
While these measures give us a sense of what the new normal will look like for both businesses and customers, it remains to be seen to what extent consumers will now embrace the physical shopping experience.
The new norm is online shopping, and by looking at your customer data, it will be easy to see who is now buying online. However, by looking more deeply into the data, you can identify those customers who could and should be shopping online. By leveraging customer and loyalty analytics, you can offer better customer experience to encourage your online shoppers and build an improved value proposition to attract those who cannot or will not use e-commerce as a way to shop. Through a combination of analytics and Artificial Intelligence (AI), you can look at automating some of the standard purchases, to further enhance the online experience. This could be the start of automated purchasing, and lead to retailers increasing capacity for online purchases by analyzing and identifying the right segment for ‘click and collect’ services.
As humans, many of our buying decisions are not based on logic. Emotions, trust, intuition, communication skills, internal satisfaction and culture all play a role in persuading us to make a purchasing decision. AI algorithms are increasingly integrating the ability to identify these key emotions and produce insights that make prospecting more effective for potential buyers. For those who have customer data, there are millions of data points on thousands of customers, and the different items they have bought and their behaviors. Thus, by connecting the dots using AI and machine learning, businesses can reposition their loyalty programs.
So, which generational cohort would be ideal for testing automated purchasing? My research has found that millennials like loyalty programs as they know the data derived from it can improve their experience with that particular brand. A survey taken a few years ago showed that at least 90 percent of millennials belong to at least one loyalty program.2 Sixty-six percent of millennials also stated they would not be loyal to a company without a good loyalty program.
This generation is clear about one thing – their particular consumer preferences do not fit into a demographical bucket, but rather their expectations and behaviors are such that they want a more personalized experience. AI and loyalty analytics will be crucial to providing these personalized experiences for millennials as well as the rest of your customers. Given the current scenario, loyalty analytics can help glean the right insights to re-evaluate target marketing strategies. This will mean that your offers will reach the right audience at the right time to drive improved engagement. It will also propel your revival strategy.
In his book, From CX to XC (Ex-customers), Steven Van Belleghem, expert in customer-centric thinking, says: “Fully automated (consumer) buying will happen. Once the algorithms prove that they work flawlessly, we’ll simply trust them, just like wedo today with our GPS system. Not just for the low involvement products like toilet paper, either. But for other higher involvement purchases too, like insurances or even regular travel plans.”
He adds: “But there’s also this form of buying that a lot of companies are currently cashing in on and that’s very difficult to predict and automate: impulse buying. Without it, Asos, Zalando, Amazon, Alibaba and many others would be a lot less successful. Difficult, but not impossible. That’s why, in the future, I see the automation happen in phases, according to these steps.”
Retailers who are seeking to reinvent themselves in today’s digital world need to engage in digital thinking and action. As I have mentioned earlier, millennials are showing us that there is no need to think through a purchase like previous generations have done before. As AI evolves further and algorithms work better, consumers will rely on automation to make most of their purchasing decisions, and as Van Belleghem says, not just staple food, but for impulse items as well. Imagine a digital world where you trust the algorithms enough to drop items into your basket – and not remove them like you did when your children dropped a box of sweet cereal into your shopping basket.
This crisis has shown us that the offline and online world are converging. In the U.K., for instance, the shift to online is staggering. In March 2020 alone, e-commerce sales reached a record high of 22.3 percent of all retailing as shoppers moved more of their purchases online. Online sales were up by 12.5 percent compared to a year earlier, and by 8.3 percent compared to the previous month.3 One survey in the U.S.4 predicts that in the new normal, online penetration will go up by 13 percent for apparel. But the downside is that 67 percent of respondents in the survey said they would spend less on apparel in the near future.
As emotions continue to drive shopping behavior, businesses will have to relook the digital experience. When the lock-downs began, the demand for fresh food shot up and retailers were struggling to meet the surge with bottlenecks in supply chains and inventory. This led to shortages in last-mile delivery capacity across various regions.5 My colleagues Akhilesh Ayer and Sinan Gurman have spoken extensively about the role of analytics in optimizing supply chains in their article.
In the coming months, we will see analytics, underpinned by AI, steering the retail industry’s growth. Some brick-and-mortar stores were agile enough to adapt to online channels while their physical stores remained closed. But there were many that were caught on the backfoot as they had not made the right investments to analyze their existing data and move quickly into the new normal. And then there were those who were doing well during the crisis but failed to capitalize on the opportunities to expand and grow.
Understanding your customer is more important than ever before. Analytics can make promotions, offers and recommendations relevant for each individual customer. Investing or enhancing existing advanced analytics capabilities and AI will be a wise decision to retain customer loyalty. These capabilities will help you leverage customer data more effectively along the lines of the three R’s, to improve not only revenues, but profits as well.
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