Google ‘big data’ and you’re going to be bombarded with a daunting array of articles and information – not all of it terribly useful or practical or high quality.
Which is exactly like the ‘real’ world experience of big data. There’s a lot of data out there, but without the analytics to make sense of it and pull together a whole bunch of different metrics or searches to spot patterns, then it’s just one big and dirty data soup. And most companies are currently trying to eat that soup with chopsticks.
The plethora of column inches about big data and analytics have tended to focus making the link with increased market share (through analyzing customer behavior) or increased engagement (through analyzing internal customer behavior).
Big data offers huge potential in helping companies spot new product opportunities and enhance existing goods.
Monitoring customer complaints or reviews, for example, can help spot problems in a product or service that can be rectified. So if an issue keeps cropping up in a warranty then this can be flagged up quickly and alterations made to the production line.
It is also an important tool in finessing pricing policy to ensure maximum profit, deciding for example, whether pricing is the same across all channels or where best to put promotions. Just a 1% price increase translates to 8.7% boost to operating profits, providing that your price increase doesn’t send your customers into the arms of your competitors. It’s a fine balance and analytics can improve your accuracy.
There’s a wealth of information that product managers can call on to analyze: call center queries, online customer reviews, web searches, location-based services, warranties and blogs. And that’s just the obvious.
One of the early adopters of using analytics and big data is the automotive industry, where in-car sensors can detect how well you’re driving. Gathering real-time data on engine performance could help the manufacturer detect performance issues.
As ever with big data, it’s not the data that’s important but what you do with it and in particular, what questions you ask of it. But unlike other areas of the business, where you want a specific answer to a specific question, product development needs a wider perspective. You’re not posing a research question that needs to be proven or disproved, you want to discover something new.
Instead, you’re looking for data that could point to an emerging trend or customer segment, or a particular problem that keeps cropping up and could be addressed with a new product or service.
In other words, you don’t want the data to confirm what you already thought; you want it to surprise you.
There’s also the challenge of breaking down the siloes in your company. Information gleaned from customer services or marketing could well provide useful insight about the kind of products and services they want to see. And that can prove invaluable to product development.
But if each department uses different metrics, then it makes it difficult to pull that information together and begin to make sense of it. It also points to the importance of looking at product development throughout its lifecycle.
A recent article in Forbes highlighted just how much analytics can influence not just product development, but also opening up new markets for products. The brand Nike is synonymous with trainers and sports gear. But that’s not all it’s doing. Since 2006, it’s been investing in wearable technologies like its FuelBand fitness tracker, equipped with sensors that track the number of steps you take a day and your sleep patterns.
As the Forbes article points out, by selling devices like this, Nike is actually in the high-tech manufacturing business. What’s more, because it involves downloading software onto a tablet or other device it also means Nike is in the software. It doesn’t stop there. Because of the data collected and the analysis given back, the company is also in the data management and storage business and the analytics business.
Analytics isn’t just used for internal marketing and trend spotting, it’s being put center stage in the company’s business strategy. Nike is competing against rivals on the quality of it analytics and it is has totally blurred the lines in terms of what industry it is actually in.
Clearly, there is a very good fit (no pun intended) between Nike’s sporting business and wearable fitness gear. But 10 or 5 years ago, this would have sounded like a crazy idea.
So perhaps many more companies need to be thinking not just how analytics can inform their internal decisions, but how they can incorporate analytics themselves into a relevant enhancement or totally separate product.