Big data may be one of the marketing industry’s hottest topics but unless you’ve nailed your marketing effectiveness strategy, you’re not going to get the most out of your data.
Drawing on my not inconsiderable industry experience it’s surprising how many agencies and clients do not anchor their work firmly in clear, measurable results. In a bid to keep moving in this incredibly competitive market we often justify the lack of taking time to stand still, take stock and evaluate what went before with the excuse that we have to keep moving. It’s true that momentum is useful, adaptation is essential and dogs are not just for Christmas, however, in the world of commerce (and not-for-profit), numbers are king.
In order to know where you want to go next it’s useful to know that where you’ve just been didn’t work, or did, as the case may be. Here are six simple steps for achieving marketing effectiveness.
1) What savings do we have in the bank?
If you’ve started to keep an archive of results – well done. You’d be surprised how many organisations don’t keep their marketing activity results in one place – accessible to all and relatively simple to search. This is the first place to look and compare the last campaign against your current activity. Tedious as it may be it will be worth the effort and time. If you don’t have any results try looking in Wikiresults (you wish).
2) What happened last time?
I’m sure everyone is familiar with PDCA (Plan, Do, Check (or study), Act) (1). This is a great framework to ensure that analysing what you’ve just done has made an impact against the specific criteria you wanted to affect.
Refer to previous reporting i.e. dashboards, campaign results spreadsheets, results presentations, campaign evaluation forms, case studies – whatever form the last set of activity was reported in will be useful. Ideally one or more of these formats will have come with helpful insights too – if they haven’t you need to take a look into this. Reporting needs actionable insights and implications. Take a leaf out of Mr Kaushik’s excellent blog (Occam’s Razor) and apply the 10/90 percent rule (2):
• “Cost of analytics tool & vendor professional services: £ 10.
• Required investment in "intelligent resources/analysts": £ 90.
• Bottom-line for Magnificent Success: It’s the people”.
3) Drawing out the map
Before starting anything, set your KPIs. Why start running if you don’t know where the finishing line is yet, or even if you’re in the right event. KPIs should reflect your business objectives and ideally, if you have previous results (for comparable activity), you should aim to set some targets i.e. goals which prove this batch of activity will at least be performing as well as, if not better than, the last campaign. This is how you start to build up what are known as your ‘banker’ items i.e. those (e)mailing lists, online advertising sites, key search words and phrases, influential blogs, creative work etc that have provided you with the best results so far. Moving forward the aim is to constantly strive to beat the bankers.
If you didn’t do any testing last time, ensure you do it this time. If you haven’t done it before start off with simple A/B testing and move on to more advanced forms once you become familiar with it.
If this is the first time you have executed a certain piece of activity then it will be more difficult to set targets. However, you canset benchmarksand use these as proxies until you start to build up your results base. Benchmarks for similar activities in similar industry verticals can be found via white papers, case studies and guidelines published by industry bodies. The trade press are also great sources of case studies for campaigns with published results which can also be a way of finding out results of comparable competitor marketing activity.
At this stage it’s also wise to define the outputs you need once you start reporting. Referring once again to Avinash Kaushik’s advice be clear who the audience will be for the reports and decide whether they only need reporting or whether they need analysis too (3). How many levels of stakeholders will there be and what reporting formats are most suitable for each layer? It’s likely senior management will want a handful of well-defined metrics presented dashboard style with two or three actionable insights, provided weekly or monthly, whilst the day-to-day operational team are likely to need detailed campaign reports on a daily or weekly basis as the campaign unfolds, possibly supplemented with an online (real-time) dashboard and a comprehensive presentation (final campaign wrap-up).
4) Final checks before lift-off
Just before the campaign goes live someone needs to be responsible for checking that all the key mechanisms for reporting and analysis are in place and working properly. Here we’re talking about tagging (for digital activity) and use of meaningful campaign codes. If your activity includes the creation or adaptation of a website then ensure the web analyst is passing on key metrics and insights from previous web reporting to the UX specialist.
5) Reporting and Analysis outputs
Everything should have been put in place, prior to go live, which then enables reports to kick-in at the right moment, so that timely results are produced without a last minute panic.
Whilst preparing the insights this is the moment for the analyst to discuss any key points or issues directly with the marketing or business owner. As analytics blogger Michael Notté remarks “I can go to talk with the digital campaign manager (and not just sending an email with figures) in order to share the insights. At this point it is up to the manager to decide (what action to take). My role is not to tell her how she should do her job - I would not dare to - but to provide her with insights so she can take data-informed decisions.” (4) These types of discussions with the wider marketing team are crucial as they provide the necessary business context into which these results need to fit.
6) Big Data and the sexiest job in the 21st century
If you are already implementing the five stages (and hopefully you are – as these are the basics of providing robust measurement), then you’re no doubt already keeping an eye on analytical and measurement memes. As the latest Harvard Business Review (5) issue (focused on ‘Big Data’) puts it “if the information most critical to your business resides in forms other than rows and columns of numbers, or if answering your biggest question would involve a “mashup” of several analytical efforts, you’ve got a big data opportunity”. And, echoing Mr Kaushik’s point from earlier “Much of the current enthusiasm for big data focuses on technologies that make taming it possible … (i.e.) related open-source tools, cloud computing, and data visualization. While those are important breakthroughs, at least as important are the people with the skill set (and the mind-set) to put them to good use …” – enter the ‘Data Scientist’. That stage, however, is for another day.
2 Kaushik A, Web Analytics 2.0, (2010). Wiley Publishing Inc.