- Perry Williams: Hello Dear, I am strongly agree with your point that the web analytics is associated with the social...
- Philip Sheldrake: Nice overview Marianina. I wanted to post a link to an article in Business Week from June about the...
- Luisa Woods: Hi Marianina, I think you make a very good point about the importance of segmentation. I like to carry...
- Eric T. Peterson: Marianina, Nice to have seen you Monday in London! I just got this post so perhaps something odd is...
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My Blogger Friends
Marketing performance management (MPM) has begun to be bandied around quite a lot as an acronym for web analytics and it (finally) has begun to be taken seriously by numerous marketing departments. Marketing performance management sounds very grand and is how we would like to imagine it should be “wow, now I can analyse and act on my marketing data to improve my site/sales/customer engagement etc.” – a holy grail for switched on marketers. But web analytics with the best analysis in the world isn’t a “get out of jail free” card. Here are three things to look out for from either an analyst or company perspective.
We’re not there yet…
Scenario 1 – our data sucks, so let’s get over it – collaboration
For example, we are using the most high powered analytics solution on the market to measure all online visitor activity. However, we’re not getting our true conversion rate due to offline sales generated by the web that aren’t being tracked – visitors that search for the products online and then complete the sale over the phone (this frequently occurs for complex products such as mortgages). And, although call centre staff have been trained to ask where the customer completing the sale came from and then input 3 for website (into their telephone tracking system that links up to the analytics solutions) how many actually do (input 3 and/or have these systems in place)?
Before I start, if we recall that Walley is blind and Dave is deaf (they have to collaborate) and together they stop the criminals getting away with it (stop the lies) and clear their names (with persuasion). Read on to find out why on earth I am mentioning the storyline of this film and hence the blog title “see no evil, hear no evil”.
What about visitors that delete their cookies so we think they are first-time visitors but they are actually returning? (Comscore released a report recently saying that nearly 30% of visitors delete their cookies but this may also be overstated because they have a competing system of measuring visitors they are trying to sell). There are other unquantifiable elements that I haven’t mentioned/thought of here.
Unfortunately for the analyst, it is impossible to ascertain with 100% certainty what is the perfect data/true conversion rate from the site alone. So we move on and try to come up with assessments that allow for other hard-to/non-measurable elements to be included in the “big picture” – be that through better data integration, assumptions or probability theory.
eg P(A) = The number of ways event A can occur
The total number of possible outcomes
To get the full “web analytics” picture, we need collaboration between different sides of the business and the context in which activity is occuring.
Scenario 2 – conflict of interest means good advice goes out of the window – lies
The analyst works for a respected online advertising/search agency. As a result of analysis, it is discovered that PPC/banner campaigns are generating a much lower conversion rate than referrals and direct and that PPC banner campaigns have a much higher bounce rate (visitors who spend less than 5 seconds on your site).
Three wise monkeys – see no evil, hear no evil, speak no evil
Does “we will use this search data to optimise your spend” ring any bells? Search marketing agencies are making commission from the search engine on their PPC spend and the creative spend from any banners created. As a result of which, the analyst is inevitably compromised and will tell the truth from the context of “let’s optimise” but may not mention what might be best for the client – eg your organic traffic is being destroyed by our PPC spend on brand keywords, let’s cut PPC spend as it is unnecessary. Or, PPC/banner traffic has a much higher bounce rate than other traffic sources, let’s cut our spend.
With compromised advice, the true value of analysis and of the analyst has been removed. So, in my opinion it is much better to have an unbiased analyst who is on your payroll for that reason alone.
Traffic Source Conversion rate % Bounce rate % Total visits
Direct 6.1 19 27,000
Organic 3.4 23 14,599
PPC 2.8 54 12,200
Banners 0.2 52 3,129
Referrals 8 21 7,802
Scenario 3 – insights need persuasion to make them a reality
Often great actionable insights generated from site analysis aren’t enough to get buy-in from our boss/client. Until we can convince others of our insights’ value, they are meaningless. There are plenty of people good at crunching numbers but I believe the real value is in the ability to persuasively present that data and persuasively push through the changes needed to improve one’s marketing performance. Without persuasion, one may have insights about what could or should be done but it is only when action is taken, that web analytics is truly transformed into what it would like to be “marketing performance management”.
The conclusion – how to get web analytics working better for you
In conclusion, we collaborate with different parts of the company/data that aren’t talking/integrating to one another (just like Walley who is blind and Dave who is deaf work together), ignore the tall stories from our search/marketing agency (we stop the criminals getting away with it) and realise our goal by using persuasion (in Walley and Dave’s case, clearing their names).
The end result is a better platform using web analytics from which to manage our marketing performance.
I welcome your suggestions, feedback or even complete disagreement so please let me know your thoughts. Apologies in advance if you found this blog post a little long and I do hope that someone out there actually reads the whole thing.
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