Big Data For Small Players: More Bang For The Buck

by Ashish Kasi, Chief Technology Officer, Capillary Technologies

Mention ‘big data’ to any small and medium sized business and the instant reaction is probably, “Oh! But isn’t it expensive and bit complicated?” This apathy is a result of the misconception that implementing a big data solution is not only technically complicated but can also eat into marketing budgets to a great extent. If you are a small retail setup with limited IT resources, setting up a standalone big data platform might be challenging. However, there are several cost-effective data analytics tools and open source software and data management applications available in the market today. You probably already use Google Analytics to get useful data regarding your online customer footfalls. Now, additional data tools can help you closely study your customers’ buying history, purchase patterns, and other parameters that can assist you in formulating relevant strategies to give them an enriched shopping experience.

Cloud and Crowdsourced Big Data Can Provide Big Value

The proliferation of cloud based platforms and the advent of crowdsourcing can be advantageous in helping you deploy a big data solution for your retail business. You can gather important data pertaining to your customers from:

  • Cloud services (Birst, GoodData, Amazon Redshift, Google BigQuery, Google Analytics)
  • Public data services (government data, Google trends)
  • Visual analytics (Tableau, Datameer, SiSense, QlikView, GraphChi, SkyTree Advisor)

And you don’t need to hire dedicated in-house IT staff for this. There are several external analytics consultants who can analyze the data you have procured and give you relevant insights.

Use Analytics and Advanced Technologies for Cross-channel Optimization

According to an eMarketer report, about 77 percent digital buyers will either use smartphones or tablets by 2017 – a trend you can capitalize on by deploying advanced technologies and data analytics solutions. For instance, store assistants can utilize smartphones and tablets to track customer footfalls and other online purchase behavior and use this information to give customers more personalized experiences in future. Even small technology investments – such as one tablet or smartphone per store – can help you tap into the huge pool of online customer data. Analytics can also help you optimize cross-channel customer experiences by tracking purchase behavior across multiple channels such as mobile and website. By identifying a customer’s specific preferences based on an earlier visit, you can make relevant product suggestions to facilitate future purchases.

How Predictive Analytics Can Help You Cross-Sell and Up-sell

Cross-selling and upselling are invaluable mantras for any retail outfit – big or small. Small retailers especially stand to benefit by making the right cross-sell/upsell offer to the right customers at the right time and through the right channel. Predictive analytics – mining available customer data and processing the same to glean pertinent insights that can fuel key business decisions – can be a big boon to the small retailer. By studying customer preferences, purchase frequency, and buying behavior, analytics can help you effectively cross-sell and upsell to your primary customer base.

Big Does Not Necessarily Denote a Number

Though there is a lot of hoopla around big data, you need to remember that it is just a means to the end. Big data doesn’t necessarily imply huge customer datasets alone; it actually denotes how you interpret the existing data available with you by asking the right questions. Small retail enterprises are quite often challenged by a lack of adequate data on customers and this is specifically true in case of retail chains where personal touch is missing. Harnessing available data from previous customer visits will help identify distinct patterns and enable you to devise appropriate CRM strategies. Then again, relatively smaller datasets gathered from CRM portals and e-mail marketing campaigns can provide useful customer insights. These days, the advent of social media has made it possible for small store chains to be a part of the online chatter and listen in to what their customers are saying about their brand. In essence, it is all about mining the data you can acquire from multiple touch points and utilize it to formulate effective customer engagement strategies.

Whether you are a small retailer or a large chain of stores, it all boils down to how you can drive deeper customer engagement and enhance brand loyalty by giving your customers a delightful shopping experience. Big data can help you get a bigger picture of your customers and their individual buying behavior. By listening attentively to the story your data tells you, you will not only benefit from a greater knowledge of your customers, but also be able to determine brand equity and relevance.