Marketing is no longer an art. It’s evolved significantly in the last decade into a scientific discipline based on balancing performance against KPIs and metrics. Where hunches and instincts once ruled decision making practices, ecommerce directors and marketing managers now already have all the data they need to make their next marketing move even smarter.
So why do so many still lack the ability to make informed, precise decisions?
In my experience, there’s a real need to embrace the science behind customer conversion and retention, and in turn, reap the benefits of smarter decision making. A marketer’s gut feeling is not without its benefits, but combine this with understanding and using data effectively, and the modern marketing arsenal is complete.
If 2014 was the year of big data, 2015 should be the year digital marketers understand it and automate engagement based on science. To best scale consumer shaped data mountains, marketers should use smart metrics to aid decision making.
I believe the best metrics to help marketers tackle this are:
Predictive revenue
Knowing the future lifetime value of customers in each lifecycle stage can help evaluate how much to spend in order to convert, retain or win them back. Predictive revenue can provide insight into the gain and loss of these customers by combining the revenue generated by conversions and the future changes to customer lifetime value. Marketers can understand how the conversions, or lack thereof, within each group will affect their bottom line, helping them decide what the next move should be.
Predictive modelling also allows marketers to forecast the financial implications of sticking with the same strategy and campaigns or switching things up. If a defecting buyer is 15 per cent likely to convert, and an inactive buyer is two per cent likely to convert, it’s clear that money, time and effort will be better spent on defectors. These might only be predictions, but they are accurate enough to use as guidelines, especially when comparing different strategies or segments and providing a view on the revenue impact of actions (or lack thereof).
Purchase patterns
By examining purchase related behaviour, such as which products and categories are most often involved in conversions, marketers can target contacts more accurately. These also provide insight into the time lapsing between purchases so marketers know the appropriate timescales to approach customers with incentives.
Predictive analytics could demonstrate that if first-time buyers do not make a second purchase within 47 days, they are more likely to defect than to buy a second time. Thanks to real-time data, marketers now know where the watershed lies and can bring second purchase incentive programmes forward.
These metrics are based on sophisticated learning algorithms, meaning they are constantly evolving. Who can say if the watershed will move over time, or shift during the year? By using smart metrics marketers can keep tracking the results against business goals and make appropriate changes to suit schedules.
Engagement patterns
These metrics quantify engagement related metrics, showing which customer engagement strategies are the most successful in terms of responses and conversions. By tracking the time between online behaviours, such as email or website activities, the optimal sending times for campaigns can be determined.
Benchmarking
In the ecommerce world, industry data consistently shows that the majority of revenue still comes from first-time buyers that have not bought before and most likely will not buy again. We are constantly analysing customer data and on average only 8 per cent of customers generate 41 per cent of revenue (The ROI from Marketing to Existing Online Customers, Adobe, 2012). Benchmarking will determine exactly how well campaigns are doing and also the efficiency of marketing changes over time. Good retention automation platforms offer reporting that does this and also measures the impact of retention automation.
Effective use of data will result in more profitable customer relationships. But often the more customers a business has, the more difficult the process becomes to manage. As marketers make sense of the science behind their data they can begin to focus time and creativity on coming up with new ideas. The latest platforms allow marketers to get to grips with data simply – doing the hard work for them.
The era of marketing instinct + data is here and it’s high time marketers realised that this = gold dust for 2015.
