We are already in the week of the long awaited Black Friday. With such a special date coming up for brands and consumers, we couldn’t help but prepare some special content to help entrepreneurs who want to participate in this event, right?
To continue the series of Black November articles, this time’s guest is Elcio Santos, CEO of Always, who wrote an article talking about the importance of Retail 3.0 and Data Science and the surprising result that this combination can generate.
Imagine the following scenarios:
● A supermarket that delivers personalized offers to each of its customers not just through digital channels but automatically during the checkout transaction—increasing sales, shopping visits and customer retention.
● A collaborative marketing portal where partners create content and promotions for different buyer segments, measuring the effectiveness of each action and each channel.
● A new distribution model that provides real-time views of inventory movement from manufacturing to the store’s delivery dock and achieves significant cost reductions by accelerating the distribution cycle, reducing inventory and creating new store-level efficiencies.
● A state-of-the-art system that makes shopper data actionable and automatically creates extensive shopper segmentations based on behavior and achieves improved ROI by integrating traditional product category management with customer category management.
● Time and location based mobile marketing services capable of communicating a lunchtime sale to a shopper’s cell phone one kilometer away from the store at noon – the system then proceeds to deliver marketing promotions based on where the buyer is in the store.
● And imagine what happens when you start to connect these seemingly disparate pieces, when you start to leverage the synergies that can be created across the entire supply chain, both in product efficiency and marketing effectiveness – all with the individual buyer as focus.
Congratulations! You have just imagined what Retail 3.0 is.
In this new ecosystem, the focus is on the individual buyer. It is built on real-time marketing and supply chain synergies built on a database of identified transactions. And that requires integrating online and offline channels, logistics and data across a value chain.
The approach strategy, therefore, ceases to have to do with the interaction channel and starts to really focus on the customer. There is no longer an abstract customer purchase journey and it becomes important to know the concrete purchase journey of each customer. And thus, the effectiveness of the approach will depend exclusively on how prepared we are to use disciplines such as Data Analytics and Data Science/Engineering.
It’s a perfect match, with impressive results. When it comes to niche retail, according to the experience of the Company Expert consultancy, having data on who your customer is and how they behave can result in an increase in sales between 30% and 50%.
And even when it comes to mass retailing, where the fight is mostly in the discount arena and every penny counts, data-driven initiatives have shown a growth rate of over 3%.
This is something that was previously unheard of, in the words of Stacey Widlitz, president of SW Retail Advisors, when analyzing Target’s sales growth – 3.4% – compared to competitors.
How to ensure Retail 3.0 hits the targets
It is not enough to have the right tools, it is necessary to structure all processes and routines from a new mentality, in which the customer is in fact king and his sovereign will. In this sense, it is important to master the so-called key technologies.
1. Omnichannel approach
An omnichannel shopping experience extends from the brick-and-mortar store to mobile browsing, e-commerce, on-site storefronts, social/digital media and other cross-channels. According to a study featured on Customer Think.com, companies that implemented an omnichannel approach saw crucial benefits for their long-term success – they increased their customer retention by 89% and annual revenue by 9.6%.
2. Chatbots and other AI and ML based tools
It is necessary to be prepared to deal with voice assistants, robotic assistants, delivery via drones and, mainly, with the so-called customer chatbots, which offer instant and 24/7 support, for information searches, order tracking, complaint management and post -sale. In addition, connected with the companies’ CRM, they can guarantee a personalized experience. Cars24, which sells used cars online, uses a chatbot to answer frequently asked questions, such as the vehicle’s age, to ease stress on contact centers. The initiative reduced call center expenses by an impressive 75%. In addition, interaction with the chatbot results in 1/3 of sales.
3. IoT-based devices
Retailers today are already dealing with security sensors, sensors to track the status of on-sale inventory (temperature, strength, etc.) and network monitoring. Now they also have to deal with other devices with technology to track the digital customer journey and beacons, adapting the purchase process to each individual shopper. Thus, customers can receive personalized offers, assistance in finding products and easy checkout – and increase the propensity to spend more by about 40%, according to the consultancy Built.In.
4. Location-based services
From previous devices, it will be possible to know when specific customers are in the store and trigger, for example, real-time alerts for an employee to go to a store location.
store to assist a customer. On London’s Regent Street, around 100 retailers – including Karl Lagerfeld, Armani Exchange and Brasserie Zedel – have installed sensors that trigger personalized offers via a cooperative app. This combination of ‘geofencing’ and artificial intelligence (to personalize offers) increased sales by 7.4%.
5. Self-Checkouts
These are machines that offer mechanisms for customers to complete their transactions without having to use traditional teller machines. It is essential to implement checkouts based on mobile applications, facial recognition and other technologies to simplify purchasing processes. A Raydiant study of self-checkout experiences found that nearly half of customers will use self-checkout almost exclusively when it’s available.
6. Modelo Click and Collect
This model that basically allows you to buy in the store and receive it at home, buy online and pick it up in the store, buy it online and return it in the store, buy it in the store and return it by mail, buy it online and pick it up at third parties, such as convenience stores and lockers. Sales of this model in the United States are expected to grow by 19.4% compared to 2021.
international experiences
Three international retailers – Future Group (Easyday), India, Alibaba (Hema), China, and Amazon, USA – took the lead and are already reaping the rewards of this authentic revolution in customer relations.
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The post Black November: Retail 3.0 and Data Science could be the perfect marriage appeared first on ADNEWS.
