Most businesses now have a fairly good understanding of what their online media is doing to drive leads to their site, they have a good view of how their site is doing at converting those leads, and decent knowledge of how they are retaining the customers they’ve already won.
Obviously, this requires a vast amount of data to be collected, processed and analysed before any useful insights can be drawn that actually result in improvement and optimisation of web marketing, site design or customer retention strategies. Once the insights begin to be leveraged, though, the benefits can be huge. For a big online retailer, a difference in its site conversion rate of 0.1% can mean a difference of millions of pounds in its revenue.
So, apparently ‘Big Data’ is a big deal, but not for the reason that seems to be assumed. Rarely does looking at information in this way result in a wholesale change to the way a company does something. The reality is that through practice, and trial and error, companies had actually gotten pretty good at doing this stuff anyway.
What these datasets tend to add is the insight to be able to tweak and optimise business practices that are already working pretty well. So, rather than making one huge data-driven change, business tends to adjust 100 smaller things, each of which helps to drive overall improved efficiency. Improving efficiency tends to be the aim, and while there are issues with looking at things purely in those terms, from an overall business perspective it can be a useful way of thinking about the application of data.
So, where are the efficiency gaps? Assuming a business is doing all it can to leverage these datasets, what else can be done? What if we were able to track customers from the media that won them in the first place right through to how CRM strategies encouraged repeat custom? Essentially, for most online businesses, we’re talking about three datasets here, and they are broadly focused on three different areas: media (finding customers), site analytics (converting customers) and CRM (retaining customers), and all too often they are held in silos, and sometimes in completely separate parts of a business. Surely you only have a proper 360 view of your customer if you can join these datasets together.
Let’s take a (very) simplified example, your media data tells you one type of keyword is driving more sales, more efficiently than another. Fine, you just increase your bid on the good keyword to buy more clicks, drop the bad one from your plans and the efficiency of your media campaign improves, fairly simple and good use of the data available. A few months later you notice a dip in your customer retention figures and no one knows why. You haven’t joined up your customer data so you can’t see that while the second keyword looked weak in terms of one-off sales, the customers it was winning for you were of a much higher quality and so the keyword itself was definitely worth its place on the plan.
OK, so it’s rarely (if ever) going to be that simple, but I would guess it’s fairly obvious that being able to join up data in this way can deliver strong benefits and efficiencies to any business. What type of media drives the best customers? What site activity is typical of big spending or return customers and how do one-off customers tend to behave? What if you were able to tailor site experience to different types of customers, target different offers towards those who are likely to form a long term relationship with your brand, and those who a likely to be less loyal? If we are thinking about efficiency savings, surely we’ll never be able to do as well as we might without this information.
The benefits are fairly clear but, as is so often the case, it comes down to whether those benefits are ultimately worth the extra time and expense it takes to gather the data. The answer to that depends on size and nature of the individual business, though I find it hard to believe that any big online retailer won’t find strong ROI in developing a truly 360 customer view, yet, in reality, it’s fairly rare to see.Global Desk Editor