It has been interesting watching the rise of the phrase ‘big data’. Some see it as a big, scary, unwieldy thing and others see it as the analytical Holy Grail that can deliver magical results but remains allusive.
While the term big data is thrown around often, not many businesses truly understand its meaning. Here are a couple of definitions to clear up misunderstandings:
- Big data: noun – extremely large data sets that may be analysed computationally to reveal patterns, trends and associations, especially relating to human behaviour as well as interactions
- Big data: Wikipedia – a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualisation and information privacy
- Big Data: IBM – every day we create 2.5 quintillion bytes of data, so much that 90 per cent of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information; posts to social media sites; digital pictures and videos; purchase transaction records; mobile phone GPS signals and more. This data is big data.
So let’s accept that big data is:
- out there
- needs to be used in businesses – big and small.
The truth is most retailers in Australia aren’t collecting any data at all, let alone tapping into big data. With this in mind, let’s look at the baby steps that can start businesses down the big data path.
Retailers require the following to get started:
- a Point of Sale (POS) system, preferably including inventory management
- an e-commerce website
- active social media accounts
- a customer loyalty program.
Many of these tools have built-in analytics and business-building tips that can be leveraged. Customer details need to be collected via a combination of POS, online and in-store. While collecting data is the best way for retailers to begin their big data project, that data is useless unless it is analysed and used. Here is a run-down of some areas in which jewellers should be aiming to capture data:
Customer behaviour
- the campaigns and programs to which customers respond
- the times when customers are active
- customer preferences and buying signals
- email subject lines that customers like, click and open
- any customer activity online.
Sales
- average sales value
- average sales value at different times of the day and on different days
- tweaking store opening hours to match sales/customer behaviour
- the performance of individual sales staff
POS/customer
- how often customers purchase online versus in-store
- the average sale per customer
- customer preferences and shopping-basket assortments.
Website
- which pages customers visit
- how long they spend per page and on the site overall
- where the customer was before landing on the site
- customer behaviour – do they respond to specific pictures or text?
- online sales per customer (if appropriate).
Social media
- do customers respond to sales incentives on social media?
- what customer conversations are occurring on social media?
- which posts have the most engagement from customers?
- what other sites do customers ‘like’?
Staff
- train staff to collect and analyse customer data using the in-store tools
- provide tablets to enable staff to use these tools and access information on customers they are serving
- get technical staff to train and supervise other staff to be more productive.
Jewellers will be better and more profitable by analysing the areas discussed and basing business decisions on the information and data they collect. Ultimately, data collection and analysis will enable businesses to use personalised information to better interact and communicate with customers. In turn, this creates a more loyal customer-base.
Big data shouldn’t be daunting for jewellery retailers but rather embraced as a tool that can help create better connections with customers and thus improve sales.