Analytics in Retail – Forging an Immersive Customer Experience

15th July 2018

From a consumer-driven industry to a data driven one, the overall retail store experience has today become one of strategy and purpose. Data is the new asset class. And its analysis can be the competitive edge businesses are seeking. The future of the retail industry is reliant on data-driven growth and analytics sits at the core of this transition, with industry benefits such as cost effectiveness and optimized products ensuring a better consumer experience.

The analysis of data-driven consumer behavior has significantly tackled several challenges through the value chain, resulting in better revenues and enhanced customer acquisition and retention. The retail segment generates humongous amounts of data, which presents a unique set of issues and challenges. Having the right set of systems and tools to analyze this data provides retailers with a rich pool of insights that can guide a better understanding of customer needs, as well as create a more efficient response mechanism, resulting in a holistic and satisfying customer experience.

The global retail analytics market is poised to double in size between 2015-2020 as per MarketsandMarkets, with a predicted valuation of $5.1 billion at the end of this period. This underscores the role of technology in spearheading the growth of the retail sector.

Given the fact that retailers need to be one step ahead of their consumers, their efficacy will depend on the way they bring together internal and external stakeholders for a seamless experience. And analytics is going to be the biggest differentiator in the way forward.

Retail analytics and their impact on customer experience

• Increased product sell-through rates

Optimised product management in retail stores is the key factor in enticing and managing consumers. The use of data analysis to match product relevance, visuals and pricing with existing or potential customers is possible by analysing consumer data. By tweaking product offerings based on analysed data sets, product sell-through rates are overwhelmingly increased.

• Efficiency in discount distribution

A majority – 90% – shoppers use discount codes for their purchases. The current scenario of discount offerings gets customers into the door but isn’t effective in building customer loyalty. The differentiating factor would be in using analytics to study historical data, and predict the impact of various offerings in the longer run. The leveraging of this data makes the application of this discount strategy more profitable, and affords better customer experience.

• Reducing churn rates

Customer loyalty is what drives retailers in the long-term, as acquiring a new customer is six to seven times costlier than retaining an existing one. A premium is therefore placed on the ‘number of lost customers’ or ‘churn rates’, as a measure of profitability and scale. Data analytics helps retailers successfully determine what customers can churn and devise new strategies to retain them or find similar newer profiles.

• Customer lifetime value

Predicting a customer’s lifetime value gives retail brands the power to advertise to them more effectively which affects bottom-line. What a customer is likely to buy, how will he spend, which are oft-bought items when predicted by data analysis ensures existing customers stay loyal to the brand. In retail this is particularly impactful, since acquisition costs are considerably higher and competition exponential.

Retail Analytics Solution – Microsoft Dynamics 365

Microsoft Dynamics 365 for Retail is an end-to-end analytical solution for the retail industry from Microsoft. The solution unifies commerce on a single platform, offering comprehensive support on sales, merchandising, inventory and channel management to enhance customer experience, increase profits, retain customers and bring about effective collaboration between various touch points. To know more about the solution and how it can help your business, reach us at marketing@levtechconsulting.com