The volume and depth of data collected by many retailers certainly continues to expand at an unprecedented rate. Combined with the exponential shifts in consumer behaviour, this means that just knowing your customers’ names and email addresses to handle communications with the market belongs to the past.
To thrive in retail, you now need to identify what your customers want and the challenge is to gain clarity about this information before they do. This will help you to figure out how they will see the world in the future, and then align your offering accordingly.
I’ve observed two distinct patterns that prevent retailers from attaining this level of analytical foresight, despite having the latest tech at their disposal:
- Most retailers still don’t have a single view of their customer data, including all customer transactions. With such a handicap, attempts to perform effective analysis will most likely fail.
- Few organisations recognise the difference between data and information, yet it’s the latter that can generate additional business. Unless you learn something you didn’t know before, it’s not information – it’s just data.
The BIG difference between data and information is that information is actionable, data is just ones and zeros. So, I implore the industry to start talking about Big Information rather than Big Data. The latter is just a challenge, not a solution.
There’s a huge opportunity in the market for retailers that achieve a single view of their data and then develop the analytical aptitude needed to distil information from it. The competitive advantage of being able to foresee customer behaviour and use these insights to build individualised, insightful relationships is a game changer.
A lesson from Silicon Valley
Whether it’s Google estimating your travel time to work, or Facebook curating newsfeed updates, or Wemo automatically switching on the lights at your home when you pull into the driveway, we’re constantly reminded that today’s technology giants have developed tools that allow them to extract information from the multiverse of data, and then act on it.
Their actions aim to be useful to you and in the process build a relationship with you. They recognise that understanding your behaviour allows them to create experiences that feel authentic and human. Think about how powerful this information-driven strategy can be in a retail environment, where customer centricity is now so crucial to remaining relevant.
I stress again that it’s the information (not the data) – the change, the new state, the actionable insights – that provides the clues to next-level customer engagement. The days of collecting static data and feeling proud because of the large number of customers recorded in your database are over. A phone book has millions of entries but is no longer relevant. It’s not the size of your database, but rather how well you can use it.
Retailing in the next decade
Contrary to prevailing beliefs, it doesn’t take massive budgets or the latest technology for retailers to master the art of extracting information from their data and in the process transform their business into a next generation, intelligent retail operation.
To get there, you must start with fortifying the integrity of all your data and this requires system and database consolidation – moving away from disjointed, siloed business systems and adopting a “one business, one system” philosophy for all retail functions.
By architecting your IT environment to be as simple as possible (simple meaning the absence of non-essential parts), you’ll lower your costs and progressively achieve purity of data. From this solid foundation you can then unleash the smarts required to generate information that will help you anticipate your customers’ needs.
Big Information in action
The retail business case for Big Information is a compelling one – maximum sales at maximum margin, with strengthened customer engagement through individualised communications and surprising foresight.
Running on data alone, it’s near impossible to optimise your margins when running promotions, and, without a single view of your customers you increase the risk of frustrating them with duplicate or irrelevant offers. From a profit perspective, in many cases you end up providing discounts to customers who would be willing to purchase your products at full price anyway.
Once you’ve tapped into the holy grail of Big Information, you can target your offers to the customers that are most likely to be influenced to change their purchasing behaviour.
For example, if you sell art supplies with the handicap of fragmented, un-distilled customer data, you’re forced to run generic promotions such as 25 per cent off canvas for all customers. But, this type of offer erodes your margins.
But, with a single view of all data, you can extract knowledge about your customers purchasing habits, such as:
- Who is buying canvas only?
- Who is buying related products such as oil paints and brushes, but not canvas?
- How often they’re purchasing the above products from you.
- Their average basket size.
- Contact the customers who have been buying canvas only with an attractive, short duration offer on paints and brushes. “Try us out!”
- Contact customers who bought oil paints and brushes but not canvas, and offer them 25 per cent off to try your canvas. You will lose some margin, but it would be margin on sales that you wouldn’t otherwise make.
- Automate your offers to align with purchasing patterns to increase basket size e.g. beauty products often have a predictable replacement window, so you can capitalise on this cycle to deliver automated, personalised offers to promote repurchase and upsell. Once setup, you won’t have to think about it, but your customers will feel as if the offer was designed just for them. You would’ve achieved the ideal customer perception that they exist in ‘market of one’.
Of course, the above are over-simplified examples. Once you’re leveraging Big Information, you unlock a wide range of information-driven customer engagement models. Amazon continues to spearhead innovation in this space with initiatives such as personalised offers, book recommendations from Kindle highlighting, and anticipatory shipping. The Amazon machine feeds on Big Data but it is driven by Big Information.
Another benefit of becoming masters of the Big Information domain is that analytical mastery frees humans from routine tasks related to customer management, allowing them to be refocused on decision making and conceptual work.
Winning and retaining customers in this new era requires high quality, integrated data, combined with the analytical savvy to extract information that can be used to enhance customer relationships and to defend your margins.
The alternative is to keep running blind, trying to patch up your systems the best you can and make sense of an incomplete picture of reality. The results of companies such as Amazon demonstrate that the retail super power of knowing the future is preferable.
Justin Cohen has been working in marketing and media for over 15 years, mostly in the digital space and looks after Retail Directions’ marketing direction, brand positioning, digital content and community.