Personalisation in an omnichannel world: Where do you start?by
Retail has always been a personal experience, with retailers taking pride in their knowledge of their customers. But today, with the wide selection of channels, retailers are finding it hard to maintain a single view point of the customer. This is causing customer intimacy, a building block for the retail industry, to evaporate. The most visible impact of this has been on customer loyalty levels, which are being eroded as retailers get increasingly alienated from their customers.
The paradox is ironic. Today’s technology generates more precious customer information, and tools that can create deep visibility into individual customer influences, preferences and spend patterns. Yet, retailers are not prepared to maximise this data opportunity.
As shopping behaviour rapidly changes into a non-linear model, retailers need to grasp Big Data to understand customer buying patterns and work with the customer to become their retailer of choice.
Tracking the channel hopper shopper
Personalisation is a way of paying attention to what a customer wants, then matching them with a relevant offering. Many services such as Amazon, Netflix and iTunes offer personalised content. They match product and promotions to the shopper’s past purchase history or known preferences (gleaned from past transactions, credit card data, loyalty card, CRM, social media, etc) or by extracting insights from shopping data across the customer’s matching demographic profile (syndicated data).
Customer data is now also being generated in brick-and-mortar stores, through mobile transactions, online click streams, loyalty cards, partner programmes, browsing history, social media chatter, email, instant messenger interactions, CRM and location-based services (LBS).
A customer may see your ad on television, discuss it on a social media channel, visit a store to touch and feel the product, compare prices online and ultimately order it from an online buying service at discounted price. How do you create a plan – and infrastructure – that tracks the customer’s actions across channels and brings it together to create a single view of the customer, then follow this up by personalising emails and product recommendations, and finally, tag along so that you are ever present when the customer is making shopping decisions, regardless of the channel? The answer: capture all that data and analyse it in real-time.
Technologies such as NFC, Bluetooth and RFID, can take this a step further. They can track customers by location and address them where they are. For example, if a customer has a recent and consistent history of purchasing baby products and is in the store, Bluetooth can be used to alert the customer to the availability of a new nappy rash cream or an offer on a bottle warmer. The success of such data relies on its quality and the technology to support it. Can the store’s systems identify the customer by the mobile number? Is the mobile number mapped to the customer’s loyalty card? Is the loyalty card mapped to purchase history? Does the store follow and map the customer on social media? Has the customer recently asked about bottle warmers on a social media channel? Quick check: has the customer already bought a bottle warmer so that we don’t duplicate the offer and minimise customer irritation? Can the retailer bring all this together and inform the customer using a message sent over the mobile, that the loyalty points balance + a mere £2 can complete the purchase for a £15 Innocence Bottle Warming Flask, which is in stock on aisle four?
Fundamentally, this requires a retailer to be adept at omnichannel data surfing, dipping and diving into data stores, connecting the dots, mapping customer to product availability, and skillfully aiming for the customer’s heart and wallet.
Predicting her next move, with a dose of analytics
This is where we get into Big Data to enable the retail magic: contextual, intelligent, value-based, real-time personalisation. Such data calls for special analytical systems because the data volume is massive (in petabytes compared to megabytes), the data formats are diverse and the velocity with which the data is arriving is staggering.
With the right real-time analytics, retailers are able to create a central view of a customer across a number of channels allowing them to predict what the customer will do next at a highly granular level. Big Data enables predictive analytics to put retailers a step ahead of the customer, once again.
Analytics isn’t new to retailers - as far back as 2011, a Wipro RSI News study called Analytics Driven Retailing showed that investments in analytics had been steadily rising for 60% of the retail industry between 2008 and 2011. Today, investments in analytics have become mandatory to survival.
Analytics is based on mathematical models, industry frameworks, forecasting, the ability to process real time events adaptive learning and behaviour models combined with sentiment analysis (feedback, email, CRM, social media, etc.). Over this is a layer of business rules integrated with recommendation engines and multi-channel customer management tools. It is clear to see that old-school data management processes, skills and tools would fail to manage such levels of complexity.
The technology to manage Big Data and analytics (such as Hadoop and MapReduce) is relatively new. It integrates servers, networking and storage into a single appliance to enable multiple queries for rapid real-time extraction of insights.
Personalisation – an interplay of devices, technologies and processes
Both the marketing cycle (path-to-purchase) and sales cycle (order-to-cash) need to be assessed and linked so that data can be shared effectively. The challenge is to transition across the interactions from research to the buy decision to returns management and CRM, cutting across channels.
Retailers have inevitably embraced technology, e.g. sophisticated in-store displays, loyalty cards, mobile marketing, RFID, video surveillance, etc. However, historically they are cautious of new technologies. And streaming data and analytics is brand new. It is a complex job, but those who place extreme personalisation at the centre of their strategy now will reap disproportionate rewards, catapulting themselves leagues ahead of competition.
Putting personalisation into practice
Every plan starts with a to-do list. For a retailer introducing personalisation in an omnichannel universe, I recommend the following:
- Track: Every customer touch point must be architected to capture all the data that is available across channels. Mix this with traditional customer profiles, buying history, demographic data, location data etc. When you combine data types with devices, channels and customer shopping patterns, this could mean a whole lot of data capture. A 2013 Economist Intelligence Report called `The Data Directive’ commissioned by Wipro suggests that among industries retail is the least prepared with data management strategies. If your retail business gets data management strategies right, it is already on a winning streak.
- Integrate: Before you personalise products and promotions, ensure that inventory and store processes are able to act in sync to avoid disappointing the customer. This requires close integration of front and back end. Remember, it can be a long and expensive journey between the two points.
- Build trust: Hand over the control to the customer giving them the freedom to give as much or as little data as they want. Allow them to change the data when they want to. Engage the customer across channels to understand their buying nuances better. Create applications that allow customers to opt-in to share their preferences in exchange for relevant offers. Most importantly, respect the relationship and data.
Customers are expecting more, and they are willing to give more for it. Retailers must make sense of the omnichannel customer relationship. Those who can do this and personalise their offerings will create an instant competitive differentiator.
Gopi Krishnan is global head of strategy and domain consulting, retail, at Wipro.
Neil Davey is the managing editor of MyCustomer. An experienced business journalist and editor, Neil has worked on a variety of newspapers, magazines and websites over the past 20 years, including Internet Works, CXO magazine and Business Management. He joined MyCustomer in 2007.