The barriers to entry to selling online have become lower than ever as platforms such as Shopify have commodified various components of eCommerce infrastructure.
The pandemic has forced the issue for many SMEs well-ahead of their growth roadmap. This puts some entrepreneurs in a challenging position given longer-term online success in contingent on understanding how to collect and use data.
While moving to a data-led strategy will require acquiring, or subcontracting in, a new set of skills, there’s no denying this is a business imperative.
The digital space has become much more competitive over the past 12 months and, once the dust settles, it’s those firms that have a handle on data that will continue to grow.
Rather than viewing this as risk, the bigger picture is the opportunity. The value in data becomes immediately apparent when we consider the competitive advantage early adopters across different segments now enjoy, for instance Tesco in grocery and Aviva in financial services.
Don’t run before you can walk
That’s not to suggest that data is a short-cut to success. There are – of course – businesses that have invested in data and analytics that are yet to see the value. It’s generally because they’ve rushed in before they have the foundations in place.
A SME does need to have hit particular milestones before it is ready to take the plunge. However, those that aspire to grow – which is all of them – will need to invest as soon as they are ready.
In real terms, this means they should have left start-up phase and be scaling up – product fit, audience, messaging and growth strategy should be firmly in place. Most crucially, the business needs to have enough customer data to allow for meaningful customer segmentation.
Getting data ready for analytics is another article in itself, but once a business is in a position to extract the insights, the big question is where to start…?
Start with acquisition channels
For scale-ups, the most sensible starting point is typically to understand which channels and what campaigns are driving most growth. For instance, while a Facebook ad may bring more people to your website than Google Ads, those customers may engage less over time.
Keeping a close handle on this data allows the business to (re)allocate marketing budgets to the channels that bring in the highest value customers.
Solving business challenges
From here, a business can call on the data it holds to expand out to see the bigger picture. There’s no right answer as to what exactly this should be, it depends on the strategic priorities.
As such, it’s good practice to work backwards from a specific question or a problem to be solved – the more granular the better – and within a defined timeframe.
Consequently, think about what sorts of forensic insights will allow you to take remedial or proactive action to deliver growth and offer actionable insights that will help to drive efficiencies and/or improve customer satisfaction.
To put this in context, an eCommerce business might identify it has an issue with high levels of returns. It should first look at what products are being returned and why: if there’s a clear pattern – for example particular items getting broken in transit, it would make sense to review the build quality and the packaging.
If there are clusters of returns in particular areas, the fault may lie with a particular warehouse or delivery service. But if the issue is more widespread, analysis of patterns in age, gender, location, acquisition channel as so-on can create a profile for a ‘serial returner’ and targeting can be tweaked to avoid the problem cohort(s).
Peeling each layer brings in new insights drawn across departments, from marketing to operations. As such, the ‘big picture’ data should be reviewed on at least a quarterly basis to dictate what the next focus should be.
Over time, the aspiration should be to gain a full picture of the customer journey from acquisition, to delivery to customer service.
Do sweat the small stuff
While customer acquisition strategies are the primary growth driver, it’s also important to set aside regular time – at least weekly, but preferably daily – to review the behaviours of existing audiences.
Finding new customers is expensive so it makes a lot of sense to keep the ones you do have on-side and actively nurture those that offer the greatest potential lifetime value – factors to review include average spend, reorder rates, the device they are using etc.
By the same token, there’s little point in expending too much time and effort on those that are low value and/or likely to churn.
These reviews should be aligned to predictive algorithms that can look out for anomalous trends such as sudden customer churn or basket abandonment. This allows the business to explore the root cause before it becomes a major issue, the most regular culprits are issues with the payments tool, or out of stock items.
There’s never been any doubt that data analytics would become a standard part of an online business’ standard day-to-day operations.
However, Google’s promise that it will phase out cookies from Chrome by 2022 means the inherent value of opt-in customer data will only grow over the course of the year if businesses to get their data houses in order.
There’s never been a greater impetus for online firms to get data right – and right now.
