Retail Analytics Will Propel Your Sales Revenue This Holiday Season

retail analytics black friday

The holiday season is around the corner, and retailers in most parts of the world are working towards upping their sales and marketing analytics game. Every year, during the period between Thanksgiving and New Year’s Eve, the retail industry witnesses a massive surge in consumer demand. Brick-and-mortar stores begin to bustle with people and online stores experience unprecedented levels of traffic. This also means that retailers, both online and offline, get to collect exabytes of customer data from various sources.

These data sources include transaction databases, social media channels, sensors (or beacons), video cameras, apps, etc. The efficient use of advanced retail analytics solutions to derive meaning and useful information from the data is what gives a retailer a competitive edge in the market. Now, let us discuss a few things retailers can do to make the most of the holiday season.

Last year’s customer data will bring Christmas early

The period from Black Friday to Cyber Monday to New Year’s Eve is golden for retailers. sales analyticsRetailers can significantly benefit by analyzing customer data collected during the holiday season last year. Such data analysis helps generate actionable insights that retailers can leverage during the upcoming holiday season.

Some of the useful insights that can be generated are:

  • The kind of offers and discounts that worked
  • The item categories that generated the most revenue
  • Customer segmentation with respect to sales volume
  • Ad campaigns that got the most conversions

Focusing a bit more on planogramming will improve sales

Planogramming applies to physical stores for the most part. A planogram is basically a diagram that shows how and where products can be placed within a retail store such that the likelihood of the items getting purchased is increased. Planogramming is, therefore, a critical skill in the retail space, as it boosts merchandising and sales efforts considerably.

RFID is one of the technologies that aid in optimizing planograms. Mining RFID data streams can help identify slow and fast-moving items. Such information helps store managers improve decision-making with regard to item placement. Items with good sell rates can be strategically placed such that they grab more attention from customers. Conversely, products with low sell rates can be eliminated or moved to another location as per customer traffic.

The concept of planogramming has takeaways for retail industryonline retailers as well. Online e-commerce platforms are likely to lose out on a significant number of leads if finding products is time-consuming or requires too much effort. Things like complicated navigation and poor responsiveness will ensure that visitors never use the platform again. Now that’s a lot of money lost. Retailers should use web analytics to optimize their sites (both mobile and non-mobile) such that consumers find what they need quickly. Technological advances have led to consumers seeking instant gratification, and a poor online experience certainly won’t yield the desired business outcomes.

Improving in-store experiences is always a good idea

There is more to shopping than just transactions, and this especially holds true during the holiday season. Create unique experiences, holiday-themed or otherwise, for customers with the help of technologies such as virtual reality and artificial intelligence. In one of my previous articles – Big Data Analytics and Retail – What Does the Future Have in Store? – I have discussed some of the technologies that are shaping the retail industry of the future. By using these technologies in tandem with advanced retail analytics, many enterprises are not only providing an enhanced shopping experience but also improving inventory management and sales strategy.

Also, video analytics can be used to understand customer responses in real time. Salespeople at stores can use these insights for training purposes to improve customer service. Further, store managers can determine store areas where customers spend the most amount of time.

Up your marketing game with targeted advertisements

Most consumers, particularly during the holiday season, go on shopping sprees. Retailers should use this to their advantage by making accurate and irresistible offers. Big data and retail analytics help understand buyer motivation, behavior, and sentiment.

Retailers can access customers’ web browsing data to know the products they have been looking to purchase. Also, data from consumers’ social media updates can be used to determine their interest levels with respect to specific products. Consumers often use price or feature comparison sites to find the best bang-for-the-buck product. Retailers can track this data and then send the best deals to consumers. Targeted ads, if done right, can improve sales by a significant margin.

Using BI and visualization capabilities will make life easier

BI and visualization tools can help retailers understand customer buying behavior and study how market trends vary over time. For example, the interactive data visualization below shows the share of the US in global e-sales and average online sales versus the number of digital buyers (2011-2015).

Humans are highly visual beings when it comes to learning in general. According to a TNW article, 90% of information that is transmitted to the brain is visual in nature. Also, 70% of our sensory receptors are in our eyes, and the human brain processes visuals 60,000 times faster than text. No wonder data visualization has made understanding and consuming large amounts of data extremely simple and quick for various enterprises.

Many retailers have greatly benefited by using advanced visualization techniques to understand customer sentiment and preferences. Imagine having useful insights, such as which product category is hot in which customer segment and how consumer demand is likely to change over a given period of time, at your fingertips. Such insights help retailers make effective business decisions way faster.

To conclude, it is important to keep up with growing technological advances and varying customer demands. The competition in the retail industry is intense, and brand legacy will only take you so far. We are living in an era wherein enterprises need to build an ‘analytics first culture to see continual business growth. Creating this culture will help in institutionalizing analytics, keeping abreast of emerging technologies, and, of course, multiplying your profits. To know more, check out the thought paper – Building an Analytics First Organization.

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