Hidden assets – are you making the most of your data

Not sure about you, but it seems like that for most business owners, the last few months have been about surviving and getting through lockdown in any way one could – preferably with a business still intact. But now as the ascent out of the Covid-19 nightmare begins, it’s probably time (and far more useful) to focus on what you can do now to move toward a future of your own making, rather than just accepting the possibly not-so-great hand you’ve been dealt.

Recently we came across a piece of research in the Harvard Business Review highlighting that although companies are paying more and more for quality data (and most businesses house vast quantities of the stuff), more than 50% of company CEOs felt the data wasn’t being used effectively and certainly not as a tool to fend off their competition.

When it comes to ecommerce data, estimates say we’re probably only using around 0.5% of the data available to us. Fun fact: the amount of data created and stored by the world’s organisations grows by more than 2.5 quintillion bytes a day – most of which is under utilised and potentially forgotten about over time and relegated to the back of the data closet.

So how do you make the most of your data?

Data is inherently valuable – everyone says so. BUT…in order to move from holding potential value (ie: it’s hidden away on a computer somewhere and you’ll look at it at some point) to being of actual value to your business, you have to be able to find a way to use it calculate its best and most useful meaning.

At its most basic, data analytics can be used to prove or disprove a hunch (gut feel) on what you might do next – especially in terms of new product releases. According to Hubspot 66% of all products fail within the first two years, with most not even lasting that long. But using your data well can minimise those mistakes significantly.

Determine which metrics you’re going to use, why and what for.

Not all data is created equal. And what might work wonders for one product or project, might be irrelevant for the next. Or worse, using it might give you a total bum steer. Before using any data think about if it’s appropriate for the task. Look at the timeframes of the data sets, its variables, parameters, etc. If you end up with different results to those you were expecting, ask yourself why and then go back and look at data set used. After all GIGO.

Don’t assume your data is complete.

When you dig deeper into your data, it can be easy to assume that what’s there is finite and correct. Jane Doe loves you on Instagram, but clearly doesn’t use Facebook, because she’s not either interacted with you there or given you those details. And hence there’s no point in advertising on FB. The only way to check the validity of your data assumptions, is to a: do further research, b: ask customers to fill in the blanks or c: work with collaborators (see point 3) for a more complete picture.

Can you share and collaborate?

As we’ve seen during Covid, different government and healthcare companies/agencies across the world are working together to create new insights and new opportunities. Put your thinking cap on and investigate who you might be able to co-create new value with if you pool (aka share) your aggregated and anonymised data with. Just make sure that you protect your customers’ privacy along the way.

Make sure you compare apples and apples before you use your data to make big changes.

What’s happened during Covid is a great example. If you’re comparing our most recent period against last year’s sales, costs, or anything else, you might be tempted to think your strategy is off. When it comes to black swan events like this one, by all means look at the broader data (ie: other institutions/governments, etc), but you’ll probably want to consider this as more of a blip and allow some smoothing of your data curves. For example, if your sales were trending up and then dropped into a hole (or the reverse) work – cautiously – on the trend returning, maybe just at a slower rate.

Think about personalising your data

Whilst we’ve always been taught the real value of data is in pooling all the info together (think trends and reporting), data scientists are now finding even greater value can be found in individualising the data to make it more relevant. However, given the customer buying journey is considerably less linear than it use to be – starting on someone’s phone, then moving to a review site, seeking a discount code at work, then making the purchase on a completely different device. That makes for a significant challenge to capture and analyse – but not if you’ve got a decent algorithm on your side to build a data-rich profile not only of customer segments, but individual customers. Predictive intelligence systems have been shown to improve business’ bottom lines (and quickly). Programs like Amazon’s product recommendation has seen improvements in revenues by 35% and those who adopt similar solutions see significant growth within the next 36 months.

And that’s where we can help. If you want to clear the decks of some of the pick and pack, shipping and logistics time-suck so you can focus more on improving your business for the longer term, we’d love to chat. You can call us on 02 9828 0111 or get in touch via the form below.

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