Earlier this month we launched a quick poll, to find out how you were using Database Marketing.
Focussing on actual usage in your business, today, the poll asked about outbound & inbound marketing.
Two other questions also covered use of database marketing techniques to coordinate multi-channel interactions, as well as marketing effectiveness data capture.
The first point of interest is much lower participation in this poll, compared to previous ones covering analytics or customer insight.
Perhaps practical application of data & analytics to make your marketing more profitable is still less trendy that new words & shiny new apps.
Anyway, thanks to those of you who did participate, as the answers provided give an indicative warning. That warning is that DBM usage is still behind the best practice being preached.
Apologies in advance for the poor data visualisation (with limited time available this week, I’m just using default graphs from Poll Daddy).
Here are those questions & what you’ve revealed:
What level of targeting do you use for all your outbound communications?
The options provided for answering this question, sought to capture the range of best practice espoused. We’ve covered before the benefits of using timely event triggers, predictive models & personalised content. I also added a freeform ‘other’ category, to see if there were ideas I’d missed. My expectation was to find most organisations using at least a propensity model, a number with models & personalisation and then some with event triggers as well.
The somewhat dull results are summarised in this simplistic pie chart:
As you’ll see, an equal (1/3 each) split between organisations just using propensity models, using triggers with models, or ‘other’ approach. The latter was normally expressed as something like ‘other rules’ or ‘business rules’. There may of course be sound analytics behind such rules, but the impression is given of less sophisticated targeting.
Is that your situation too? What prevents you from testing event triggers & propensity models? If you are like the third already doing that, why aren’t you testing personalised content too?
What level of targeting do you use for all your inbound ‘prompts’?
Focussing now on prompts for online customers, or for staff via service channels. This question provided the equivalent targeting options to the previous questions. Hoping to identify what mixture of predictive models, event triggers & personalised content was being used by firms.
Here’s a very similar pie chart with the results:
As you’ll see, it’s an equivalent picture to the targeting of outbound direct marketing. Perhaps that is not surprising. Firms that have the capability to use models & triggers together would be unwise not to use them for all marketing channels. One again the other, was also some form of bespoke rules for targeting (neither event triggers nor marketing).
Is your targeting, for inbound prompts, at the same level of sophistication as your outbound email campaigns? If not, why not?
How do you coordinate interactions across all your channels?
Here our focus changes to the modern-day challenge of coordinating so many different channels of potential interaction. This third question checks the level of coordination & potential solutions being used within businesses. From none (uncoordinated), through channel silo’d solutions, to true multi-channel orchestration through multiple potential solutions.
It’s that dreaded pie-chart again, sorry.
This time it represents a surprising lack of sophistication, or perhaps more correctly very polarised experience. Two thirds of respondents had either no coordination or were only coordinated within channels, not across them. The other third recorded a solution via purchased CRM or Marketing Automation software. A lot depends on the sophistication of the implementation, as few such solutions work ‘out of the box’. However, it gives more hope that some firms are coordinating their messages & interactions across the multiple channels that today’s customers expect.
Where do you sit on that pic-chart? Are you coordinating all your customer interactions, or do you still risk appearing stupid or uncaring to your loyal customers?
What feedback do you gather on impact?
This question proved our most popular. Perhaps researchers and other such professionals without experience in database marketing applications still, feel free to comment on the feedback captured on marketing measurement.
Options were offered; to cover the full spread of holistic marketing effectiveness measurement. This includes customer feedback, incremental reporting, A/B testing & employee feedback. Greater participation also revealed a wider diversity of methods used. This is reassuring as this question allowed multiple answers, because effectiveness measurement requires these multiple data points/perspectives.
Finally, a break from the pie chart:
As you can see, the most popular options are to capture customer feedback & learn through A/B testing. Hopefully these basics are in place for most firms. It was concerning to see that incremental marketing & sales reporting were less commonly used, suggesting relying on codes or attribution. Indeed, detailed marketing attribution was the fifth option selected. Good to see this, if it enables the understanding of different media contributions & has analytics evidence.
Surprising gaps were ‘profit reporting’ & ‘visits to touch-points’. These suggest that ROI is still not the norm for reporting marketing effectiveness. Are you still viewed as a cost centre, not a profit centre? The lack of visits to (or observation of) touch-points also suggests missing out on emotional context. Do you know how your customers feel about your marketing or how your brand is perceived as a result?
Thanks for participating. I hope those results & some of the questions they pose, help you to continue improving your marketing. Did they reflect how you are using database marketing or not?
If you face challenges with your Database Marketing, please feel free to share your experience here. A problem shared, as they say…