Analytics

“Number 1 app in UK, France and Germany…”. Those who regularly browse the Apple AppStore hunting for applications (apps) will undoubtedly be familiar with this type of catch phrase.  It’s generally what users first read when they land on app description pages (as if they were all number one!). Developers and designers use this type of technique to lure candid users to download the app by making them believe it’s the best of its kind on the market. This also illustrates how the success of an app is often assumed: the higher in the ranking, the more successful it is. But as you may probably know already, this approach is entirely flawed.

First of all, one can wonder how these rankings are built. As it is rarely clearly stated, we can only suppose that the number of downloads of an app governs its position in the table. But again, over what period of time? Number of downloads in the last month, quarter, year? This brings in the process a lot of vagueness and can surely not be used as a success measurement tool. Moreover, as Jakob Nielsen suggests in his column about iPhone App (http://www.useit.com/alertbox/mobile-apps-initial-use.html), users download more app than they actually need and use, which corroborates the idea that the number of downloads is not representative of the usage and can be resorted to as success criterion.

Then comes the question of the popularity of an app. App owners can write comments on the app description pages of the AppStore and rate them on a scale from 1 (negative) to 5 (positive). As a user experience professional, I strive to get the voice of the customer heard by my clients but I don’t consider it to be a viable success measurement method. Personal opinions are very subjective and tend to be only expressed when something goes wrong or incredibly well. Moreover, most of the app ratings derive from the ‘rating prompt’ that pops up on the iPhone when a user decides to delete an app. This biases the results in a negative way.

So how should the success of your app be measured? From a business perspective, the response is simple: the success of an app should be measured just like the success of a website, i.e. by defining and tracking KPI. Most of the apps provide a web-based service, which implies a digital connection between phones and web servers, just like there is a connection between PC and web servers. This allows data to be captured, such as number of information requests, conversion rates, app usage duration, app usage frequency, etc. In terms of web analytics tools, the capture of mobile phone applications usage is only at an embryonic stage but the trend is on the up and some of the current tools on the market are already capable of monitoring app usage.

Boasting about an app being the most used rather than the most downloaded would surely be more credible to end users!

In response to NMA article, 21 January 2010 Peter McCormack, co-founder of McCormack and Morrison, makes some interesting points in his opinion piece in published in NMA 21st January.

If brands are truly throwing away their traditional marketing campaigns in favour of third party channels such as Facebook then I would agree it is unwise – but only ‘today‘. Because today you cannot connect the dots and establish the identity of twitter’ers and other anonymous users of social networks, but that will not always be the case. There will come a time when total transparency exists online and your anonymity will be lost. Read more about: Connecting the dots

This article, written by Neil Mason, was originally published on Clickz.com on 14/01/10 and is republished here with permission.

In my last column I reflected on 10 years in digital analytics and how far the industry had developed in decade in some ways and how there was still room to grow in others. I commented that I thought that one of the issues was that the online marketing world had been “data rich and analytically poor” and this week I want to explore some of the areas where I think there is work to be done to enhance the quality of insight that digital marketers get from their investments in data capture and reporting technologies. Read more about: Analytical web analytics

This article, written by Neil Mason, was originally published on Clickz.com on 22/12/09 and is republished here with permission.

It’s hard at this time of year not to get a bit reflective at the year that’s gone by and to think ahead to the year that’s about to be. But it only struck me though as I sat down to write this column that I am just about to complete my first decade working in digital marketing analytics. I got started when I moved to work at an online auctions business in 2000 having spent a (large) number of years working in “offline” marketing analytics and consumer insight. I remember that when I got to this online business that the head of marketing told me to forget everything that I had learned in the offline world as this was “new media” and that “things were different” now. Read more about: Digital analytics over ten years

This article, written by Neil Mason, was originally published on Clickz.com on 04/12/09 and is republished here with permission.

 There’s the old saying that “a picture is worth a thousand words” meaning that it’s easier to convey ideas and concepts visually than through text. The majority of the sense receptors in our body are in the eyes. Some people are more “visual” than others but the visual representation of information is still one of the most powerful mediums for getting your message across. Read more about: A picture is (often) worth a 1000 words

This article, written by Neil Mason, was originally published on Clickz.com on 20/11/09 and is republished here with permission.

Last time I looked at some of the challenges around understanding the dynamics of marketing activity when using the standard “attribution” models provided in most web analytic systems. Most of the time web analytics systems use a “last click” attribution model which credits the last marketing touchpoint with the sale or conversion and can give a highly misleading view on the role that different channels play in the awareness building and consideration phases of the purchase decision making process. One approach to overcoming this challenge is to view the various different attribution models that are found in some web analytics systems to understand the role that different channels play or an alternative approach is to use data feeds to extract the data from your web analytics systems into a database and to analyse the data there. Read more about: Extracting more value from campaign data

This article, written by Neil Mason, was originally published on Clickz.com on 06/11/09 and is republished here with permission.

At the Emetrics conference in DC I picked up a copy of a white paper by Eric Peterson on marketing attribution. In the white paper Peterson outlines the challenges with marketers relying on the traditional “last click” attribution models that are built into most web analytics systems, at least as a default setting. I’ve highlighted some of these issues before in this column and it’s good to see the subject getting more attention from other commentators in this space. Read more about: Understanding marketing dynamics

This article, written by Neil Mason, was originally published on Clickz.com on 23/10/09 and is republished here with permission.

It’s been a busy couple of weeks on the conference circuit. WebTrends held their Engage conference in London and last week I was in Washington DC for the Emetrics Marking Optimization Summit . It was good to see WebTrends out and about in the market, showing off some of their latest stuff. They’ve been working hard on their messaging by the looks of it and getting a distinctive market positioning going. The core brand themes they talked about were “Power”, “Elegance” and “Openness”. Read more about: Emetrics – optimising analytics