The headlines and news stories are predictable: Bricks and mortar are failing. Online is the future.

Here at 6R, we know that this is an oversimplification, as online and in-store, experiences merge, good retailers are using data to focus on improving convenience and experience for their customers. It’s the balancing of macro trends with insight from going deep into customers mindset that gives detailed data we can work with.

Customers want retailers of speciality goods to make them feel personally important and valued in a comprehensive shopping experience.

Businesses in highly competitive fields need more than just smiling faces. They need to focus on making each customer experience a positive, unique and satisfying one. Strategic use of properly acquired data can help. We have touched on this before when we wrote about using customer data for efficacy.

Data will be the biggest driver for retailers in 2019, as stores become more astute at knowing who their consumers really are.

How Data Helps Your Business

In the digital age, when businesses talk about data, they are referring to accumulating information on customers. This information helps the companies to better respond to consumer trends and individual customer desires in both marketing and sales.

By studying various sources of data, retailers can create better experiences for their customers before, during, and even after, the shopping experience.

Businesses need to develop a competitive advantage in today’s retail environment. The increase in the use of customer analytics tools is improving customer retention and loyalty by creating personalisation at scale.

Different Types of Data

Most people are familiar with the idea of “Big Data.” Often, the connotation of this phrase, is a negative one, especially when it comes to concerns about social media data capture and the use of information from the general public.

Big data, however, can help companies and services respond better to the needs of the consumer, and transform lives for the better. For example, Australian utility organisations have reacted to the challenges of poor customer service by using big data to develop better responsiveness in key situations.

Fewer people may have encountered the concept of “small data.”  The difference between big and small data reflects that of macro versus microeconomics.

Big data refers to mass movements and trends.

Small data refers to gathering, compiling, analysing, and using data on individuals or smaller subsets to enhance their personal connection to the business. Rather than treating people as herds and groups, small data enables a more profound interaction.

“Big Data is pretty incompetent at suggesting how to increase the love.” [1]

“In the 1990s LEGO’s sales were declining and executives were scared by Big Data research studies showing that Digital Natives were increasingly distractible and in search of instant gratification. Swayed by this data, LEGO was considering dumbing down its toys, making the kits simpler and even perhaps increasing the size of its iconic brick. But then Small Data convinced LEGO to do an abrupt pivot, going the other direction completely, after senior leaders visited the homes of their young users and talked to them about hobbies and leisure.” [1]

For small or medium-sized businesses offering speciality services or products in a narrow field, big data may not be as helpful as small data. Small data is what can help them to establish lasting relationships and connections that lead to return visits, increased sales, and word of mouth referrals.  The insights into the motivation of customers, gained from small data is incredibly valuable and provide businesses of all sizes with personal and emotional motivation. An Insight that is often lost in the ‘averages’ of big data analysis.

How AI Boosts the Bottom Line

Once a business decides to collect and use data, the major challenge is deciding how best to use it. Staff and computer systems can collect information, but then what? Artificial intelligence may be the answer.  AI services can automatically help its users to master sets of data and maximise their potential, without draining their resources. Although generally identified with sifting through big data caches, AI systems and software can adapt to the specific needs of a smaller business. Retailers can use AI to lift insights from customer transaction data, providing them with information to tailor in-store offerings.

“Although the current mantra of deep learning says “you need big data for AI”, more often than not, AI becomes even more intelligent and powerful if it has the capability to be trained with small data.”[2]

Small data combined with AI technology can help retailers, to create a superior customer experience. ELSE, an Italian shoe company uses AI and data in a “bottom-up” approach. This approach uses data to target individual customers, to begin with, and then works up towards larger groups, rather than the other way around. ELSE has a virtual shoe sizer that uses simulation technology to match customer feet with the perfect shoe selections.

Data Plus Customer Service Equals Results

Data alone does not solve the problem of satisfying customers. It must conform to a business mission plan that emphasises customer service while exploring better ways to serve each customer. When great products, modern technology, innovative owners, and data (big and small) are combined, the business has the best chance to maximise its potential.

We at 6R Retail love working with businesses that are looking for process improvements that will improve their customer experience and bottom-line profitability. If that sounds like you, please get in touch.


[1] Martin Lindstrom; Small Data: The Tiny Clues That Uncover Huge Trends
[2]; Why Small Data is Important for Advancing AI