Retail: How to drive growth with advanced analytics?

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Retailers are becoming increasingly data-driven and digitally savvy: for those who are yet to adopt advanced analytics, it’s not a case of ‘if’ but ‘when.’ Failing to do so results in difficult times ahead, purely because they won’t be able to leverage predictive customer insight for new opportunities and growth that analytics can yield.

Organisations who are able to draw analytics intelligence at a faster rate than competitors can provide improved customer experience, innovate and react to the ever-evolving consumer needs at greater speed. Laggards put their businesses at risk by not embracing the opportunities of advanced analytics.

We commonly see the most successful retailers empowering data and analytics to achieve a multitude of business benefits. These include:

Improved targeted marketing

Data exists in masses for retailers to use, including online and sensor data. Competitive retailers’ IT departments are effectively gathering and organizing data now to make it accessible to the data scientists, analysts, marketers and other business-focused roles involved in delivering customer insights in real-time for the common goal of boosting revenue.

A large number of retailers have achieved a 360-degree customer view real-time analytical environment, which is providing them with a deeper level of insight used to enable analytics-driven targeting, resulting in increased revenue opportunities.

Empowered growth

The assessment of analytics capability is crucial to the initial stages of any analytics programme. The most innovative retailers know that, in addition to identifying technical gaps, it’s also essential to consider whether your analytics strategy is aligned with your business goals and whether sufficient operational and governance capabilities are in place.

These forward-thinking companies are continually adapting analytic capabilities to meet evolving needs while continuing to develop highly efficient solutions. By doing so, retailers have scalable analytics programmes that can adjust as they grow, driving better results and profitability.

Ability to meet ever-evolving customer needs

With advanced analytics, retailers can understand changing customer profiles more clearly, especially those surrounding online buying behavior around vital retail events such as Black Friday and Cyber Monday. They are learning that developing a personalized online shopping experience is key to driving sales: ‘recommended products’ by Amazon is a good example of a data-driven customer targeting strategy.

Analytics-driven insight is demonstrating how customer buying behavior has evolved, resulting in a shift from in-store purchasing to shopping online: a Shop.org survey, retail executives were asked where most of their 2017 technology investments would be: 39% chose mobile, while just 6% selected in-store.

With increased visibility into device usage via analytics, retailers can identify different customers in terms of shopping behavior, such as customers who only react to offers. Retailers can then tailor personalized targeting built into their websites in real-time so that, for example, offers are just pushed to sale-seekers of their customer base, leading to improved conversion rate and increased revenue.

What does the future hold?

Beyond shopping online at home, smart appliances will soon be able to use analytics to predict and accommodate consumer needs. Connected fridges are a crucial example of fast-evolving retail analytics in use: these appliances can already tell users what to include on their shopping lists, and even automatically order these groceries to the front door without permission having to be granted.

Retailers must act now to achieve analytics-driven success. Laggards will be unable to leverage the predictive insight that advanced analytics can yield, critical to driving business benefits and thus surviving in an increasingly digitalized industry.

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