Driving Retail Decisions With Data – More Than Ever Before
Everyone knows that Usain Bolt leveraged data analytics to set the world famous 9.58 second Olympic record, but do you know that you can also bolster your profits using data analytics to thunderbolt your retail decision making and marketing capabilities?
In today’s hypercompetitive retail ecosystem, data driven marketing has become the fiercest battleground with big players eyeing a chunk of the customer wallet. Here, data sits at the very seat of the decision making table.
The Need for Data Analytics in Retail
Voltaire said, “With great power comes great responsibility.”, and it all started with a Big Bang of customer data. Retailers possessing tons of data is like a child with a sharp knife. They cut themselves all over. They are less informed on leveraging such huge volumes and have suffered without having the right analytics for decision-making, which are business critical in customer churn and retention. A Forrester report states that, though 74 percent of retail firms say they want to be data-driven, only 29 percent are successful at connecting analytics to action. Hence, when voluminous data becomes a part of the problem and not a part of the solution equation, it becomes a challenge.
Instead, the diverse data powered with quantifiable analytics drives an expanded information access. The efficient capture and processing of data is the first step in transforming information into business insight. It’s not enough to just capture the data; it’s also important to understand what business questions and decisions the data will serve. Questions like which products drive a better basket, what is the business mix, how to forecast inventory, etc. Artificial Intelligence and Machine Learning provides the engine behind such advanced analytics, which can help companies solve business decisions and assist in combining and visualizing data for further analysis. For instance, Big Data Analysis has helped increase Walmarts Sales turnover by having sophisticated data algorithms. They analyze credit card purchasing history to provide customer recommendations based on personalization.
Good customers buy, the smart ones webroom, but great customers keep coming back and also refer others. The key differentiator lies in customer relationship and engagement across Omni channel marketing. As retailers have taken the Omni channel trajectory, tracking and managing customer engagement has become a key customer retention imperative. A Statistics Report On The State Of Omni Channel Shopping suggests that companies with Omni Channel customer engagement strategies retain an average 89% of their customers.
Hence leveraging data analytic insights bridge such gaps by drawing in data from siloed data sets, psychographics, demographics, share of wallet to create a holistic and refreshing perception of customer behavior for informed decision making.
Such advanced analytics are used to derive insight into customers’ buying habits and based on metrics like desires, buying habits, preferences and propensity to spend in a given category or price range, recommendations of products which might be of use to him are delivered both when he is shopping and also as mailers. Also, AI enhanced Intelligent personalization is a high influencer of the trend curve and is not looking at normalization anytime soon.
For example, Aspire has partnered with Episerver which has an AI powered visitor profile store and helps in building websites and ecommerce sites. Powered with in-built machine learning abilities, it captures customer information both for logged in users as well as anonymous ones, to provide ‘Personalization Services’ to drive Recommendation engines.
This is a big hit with customers. A study show 86% of consumers indicate personalization plays a significant role in their purchase decisions. Many of them are forthcoming to share their information so that it will be used to deliver recommended products which are of value to them. This curve is all set to springboard in the near future and its vertical growth trajectory is a growth indicator.
Besides, technology innovations like sensors, RFID tags, QR codes, NFC tags and beacons can drive personalized experiences and real-time, in-store promotions as customers lift the product from the shelves. For example, when customers use a store’s mobile app, approaching a display can trigger a coupon for items on display to be sent directly to the device.
Single Customer View for Stellar Marketing
An SCV is a consistent, aggregated, and holistic representation of the customer data known to an organization. It effectively integrates, captures and maintains data from all disparate sources like online and brick and mortar stores. It can then be built with demographics, behavioral analytics and social sentiments. It is versatile and holds good even if the customer database is in the millions. It simplifies the ‘Analytic Insight’ process so that you don’t need to be bamboozled by the technobabble.
Driving ROI from SCV
The significant benefit is that SCV can drive efficient and scalable business decisions than ever before. This also leads to higher profit numbers and more segmented product development. They can tailor and prioritize customer communication. Marketing campaigns can adhere to customer history and drive valuable customer insight which generates greater revenue per customer through cross selling and up selling, hence driving customer retention and churn. Also, once the retail brand starts getting better ROI from their marketing, a single customer view allows you to measure this more easily.
Hence SCV is a clear win-win for both customers and businesses alike and would hasten a seamless business decision making process.
Voice Technology is speaking up in retail
Customers are looking for deeper connections, and location and voice technology promise to be the bedrock of meaningful shopping experiences of the future. Retailers have identified that voice activated shopping assistants are becoming must haves for the millennial. The customer simply has to say the product name and the device shall give the right product result. Hence, customers no longer need to drive, or log in to the computer or even pull out smartphones to open an app. This data also can be collected for analytics and integrated using the SCV system.
Visual search resolves the conflict between the colorful exploration of traditional retail and the convenience of online shopping. This can also be seamlessly integrated into the SCV system for actionable insight and successful ventures are gaining retail traction.
Hence, Voice Technology and Visual Search are the next iteration of online shopping and its integration into the analytics engine will give more insights on customer tastes hence driving retail business decisions.
Identify patterns, Build effective Marketing Campaigns
Of course, having data is table stakes. When a customer logs in to his account, the retail analytics tracks all kinds of metrics like bounce rate, dwell time, average order value, clicks, foot traffic, conversions, exits, add-to-cart, and time to purchase.
Successful retailers should know the right questions to ask about the huge data and the above metrics act as bucket brigades to drive real time, actionable insights which in turn drive marketing campaigns. As the trend line moves from a product centric to a customer centric approach, the focus on data moves from ‘what’ to ‘how’ it is being used.
What clues have departing customers left in the past? What are the telltale signs that a current customer is likely to leave? Understanding such patterns using data analytics, not only drives personalization but is also foundational for building effective marketing campaigns and business models.
Predictive Analytics and Decision Making
Leveraging such behavioral analytics can forecast the predictive analytics which helps quantify future customer behavior so that the decision making process can be channeled and made effective accordingly. It can also be planned to forecast inventory. Amazon for instance, has the power to predict who will Click, Buy, Lie, or Die! They use predictive analytics to offer anticipatory shipping. They also use it to batten down the hatches, to wade through difficult and competitive times.
According to Zero Moment of Truth (ZMOT) research by Google, 70% of consumers research online before purchasing in-store. So Data Analytics drives the decision making wisdom of retail marketing campaigns to understand what’s shaping consumer decisions on the path to purchase. This paradigm shift in the behavioral climate of consumers should precipitate the leveraging of behavioral analytics, to condense clouds of a single customer view to rain need based products on customers, followed by refreshing spurts and showers of customized offers.
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