You may not realise that platform-provided analytics software (FB, GA, Shopify etc.) doesn’t always tell marketers and sales teams the full story. In fact, some of these external tools actively skew attribution in their favour.
Luckily in recent times, it has become financially accessible to take matters into your own hands and implement an incredibly robust analytics platform that shows you the more comprehensive truth of where your budget is going (evaluating Customer Acquisition Cost and Customer Lifetime Value).
It’s all-important to get your (data) house in order before you can expect to pull any meaningful insights from it!But are you even ready to invest in analytics? Start by asking yourself these 3 questions to see how ready your business really is:
Most e-commerce firms have already taken the plunge into analytics to a greater or less extent, but not all will necessarily see the value. Early adaptors across most segments are already enjoying a significant competitive edge gained from high quality analytics-led approaches though.
To extract enough insight to make the investment worthwhile, you do need to have enough customer data to inform meaningful decisions. In real terms, that could equate to a couple hundred transactions a day at least. In other words, businesses considering an analytics platform should be at least in the scale-up phase and have already cracked the code on the basics – growth strategy, product and market fit, messaging and so-on.
Data may lie behind the e-commerce arms-race, but rushing in to analytics without proper preparation will only waste time and effort. It could potentially lead to bigger issues down the line too.
We hear a lot about data lakes, but without having the means to access and understand it, these are more data quagmires. Extracting any use from data means first combining all sources into a single source of truth and making that readily accessible to the operators in the business.
This process may well sound incredibly ‘techie’ and for this reason, data is often laid squarely at the feet of the IT team despite them not being the end users of the platform. This creates a disconnect between the platform and the problem it's meant to be solving (Read more on this issue here).
Analytics shouldn’t be owned by IT, nor should it just be the domain of the sales and marketing teams. The true value in data lies – eventually – in being able to connect the dots between departments. However, if the analytics platform doesn’t meet the needs of particular stakeholders, they may take it upon themselves to build their own and the data becomes siloed once again.
From this perspective, no single department should take ‘ownership’ of data. Digital transformation is contingent on horizontal shared ownership so it doesn’t matter who takes the lead within the business. What’s more important is that the right people are involved from across departments and all are working towards shared goals.
The go-to data that businesses know they need is usually tied to marketing spend, especially considering the business imperative to understand what channels and campaigns are really driving most growth. Once you know which are performing best from an acquisition perspective, the next step could be to identify what existing audiences have the greatest potential lifetime value.
The more specific and the more granular the objective the better. Work backwards from a particular business challenge and consider what sorts of insights will allow you to take proactive or remedial action. If you want to reduce the number of returns, then ask the platform to look for patterns in age, gender, location, acquisition channel as so-on to create a profile for a ‘serial returner’.
At a later date, you analyse the same issue from a fulfilment perspective – how often does stock arrive damaged, from which warehouses, and using what courier firms etc?