ClickZ Articles

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

In my last column I outlined how organisations can come unstuck with their web analytics if they don’t pay sufficient attention in general to the integrity of the data they are reporting. It can seriously impact on the decisions that the organisation is making. One of the areas in particular that I have seen organisations struggle with using their web analytics tools is campaign tracking and once again it’s often the processes and not the technologies that are the root cause of the problem.

The ability to track marketing campaigns is now a standard component of any web analytics tool. We don’t need to worry anymore about having to set up specific landing pages and tracking referrals to the page. Most web analytics tools now use the same principle of campaign tracking. This involves of adding a tracking parameter to the end of the landing page URL to identify the piece of marketing activity. The web analytics tool is then configured to recognise the tracking parameter at the end of the landing page URL as a visit generated by a campaign and then populate the database and reports as appropriate. Simple enough in theory but often trickier in practice.

Some of the common pitfalls that lead to poor quality campaign tracking data are:

• Campaign data is not properly structured
• Campaigns are not consistently tagged
• Campaigns are not consistently tagged consistently

The first of these pitfalls is a planning issue. The second two are process issues.

Most web analytics tools have a framework or structure for campaign reporting. This is where a specific piece of activity is identified by a series of attributes. These attributes are then used to provide different levels of reporting. If we take Google Analytics purely as an example, then a piece of activity can be described using up to five different attributes (Source, Medium, Term, Content and Name). Part of the campaign tracking implementation process is to determine what these attributes mean for your own campaigns and how detailed you want to be. It’s important to think ahead about what activity you might want to run in the future as well and how that might fit into the framework. For example, you might be running only one type of email newsletter at the moment but if you develop your email marketing strategy to include different types of more targeted emails, will your campaign tracking approach allow you to identify how each of the different types of emails are working?

Whilst the underlying principle of campaign tracking is generally the same across most web analytics tools, the framework for reporting does differ from system to system. Some tools are more flexible in their approach than others. Whatever the tool though, proper planning is required to ensure that the right kind of reports come out the other end.

After planning comes process. Having decided how you want to structure and report on your campaigns, the campaign landing page URLs need to have tracking parameters attached to them. Sometimes this is an automated process but more often than not there is a degree of manual intervention and that’s where the problems usually start.

First of all, all campaigns need to be tagged to be tracked. This might seem like a statement of the obvious but it is surprising how often in the heat of the moment to get a campaign live, the tracking parameters are forgotten. I know that this doesn’t happen in your organisation but it does in others? Once the campaign has gone live without the correct tracking parameters attached you can’t go back and recover the data. It just doesn’t exist. And the time that you really want to know how a campaign is performing is when it goes live. So, you need to have management processes in place to ensure that all campaign landing page URLs have tracking parameters.

You also need to ensure that the landing page parameters have the right tracking parameters in place as well. For example, if you have an attribute which is “email” to identify all visits coming from emails, then it needs to be used consistently as “email” as opposed to “Email” or “e-mail” or “E-mail”. Lack of consistency in tagging resulting is poor data integrity in reporting. Again, this may seem obvious but the challenge comes when you may have different people or agencies responsible for management different types of campaign. They all need to tag the campaigns in the same way and a degree of process and control is required. This can be helped by having a centralised approach or using campaign management technologies.

So, planning and process are the watchwords for campaign tracking success.

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

It was one of those moments. I was working on a client’s data and I began to suspect that something was wrong. Not with the client’s business but with the data, but the potential business implications were very significant. Sure enough, as I dug deeper and deeper into the issue it became evident that there was something seriously wrong and I got that sinking feeling.

The story behind the story was that the business in questions was looking to aggressively improve the effectiveness of the digital channel and had been focussing on conversion optimisation as traffic levels were quite buoyant. They had implemented a satisfaction tracking survey to understand visitor intent and satisfaction; they had commissioned usability testing to understand the user experience in more detail and they had started a testing and experimentation programme. It was all the right stuff, the problem was that there wasn’t any strong evidence that conversion was actually improving. So it needed a deeper dive into the data to find out what was happening and that’s when the problem emerged. Without going into the gruesome details the impact was that the conversion rate was being underestimated and that the degree of underestimation had been getting worse over time. This meant it was a case of “What do you want first, the good news or the bad news?”. The bad news was that the historical data from the web analytics tool was wrong on some key metrics, the good news was that the conversion rate was better than previously thought.

The really bad news was actually that the business had potentially been focussing on the wrong problem. Whilst all the activity on conversion optimisation was good stuff, the revised data highlighted that other issues may have been more pressing. The other bad news was that the credibility of the data was seriously undermined and to some extent the team as well. For conversion optimisation it was taking two steps forward and one or two steps back.

The point of this case study is that it reinforces the need to get the right numbers right and to keeping them right. When it comes to marketing optimisation good quality data is a core component. Getting good quality data that allows better decision making is a key step on the journey. That might seem like an obvious statement but it is not a process that should be underestimated and nor it is a one off set up event. When a new system is implemented that is inevitably a focus on the data it is generating and that might be reconciled against other data sources. That’s great but those checking processes need to be repeated at regular processes to ensure that the data integrity remains high. If this isn’t a managed, ongoing process then there is the possibility that the integrity will decline over time until something happens which causes the data to be questioned by which time it might be too late.

Managing data integrity is a messy job but someone has to do it. Good processes will certainly help ensure that all pages get tagged; campaigns are tracked properly and so on. Technology can also help with solutions out there that will check for tags on the site, as well as solutions that help address tag management challenges. It also needs a keen eye to be looking at the data for trends and patterns that may not be a true reflection of what’s going on. I actually think this is a skill but it’s a skill that can be learned. A good marketing analysts can sense when something doesn’t look right and in my own experience if something looks odd , then it probably is odd and isn’t real behaviour. Sudden changes in trends, steps in the data, spikes and dips are all potentially symptomatic of artificial impacts on data and if they cannot be explained by real world events, then it’s worth digging into the data to see if there is anything untoward happening like changes to the tool’s configuration, new site monitoring tools being put in place, changes to the hosting environment and so on.

So, don’t see getting good data integrity as a one off event but as an ongoing process. Be wary of the potential impact that changes to your site or your tracking environment will have on your data and plan accordingly. Take time to reconcile your data on a regular basis to see if there are any divergent trends. Hopefully with these basic processes in place you can avoid that sinking feeling at some point in the future.

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

An interesting report was published recently by E-consultancy that gives a useful insight into the state of play of the web analytics industry here in the UK. They surveyed around 700 people from “practitioners”, agencies consultancies and vendors around a number of themes including the use of analytics within organisations, the amount of investment being made and the use that people are making of the data that has been invested in.

When asked how many web analytics tool they were using within their business over 50% of people said they were using two systems or more. Quite often the scenario was that a company was using a paid-for tool and then were using Google Analytics as well. Relatively few organisations were using Google Analytic exclusively. This is a trend that I have observed as well, an organisation has a system from one of the major vendors and then also deploys Google Analytics “to see what it is like” because it’s free. This result throws up some interesting questions like: “is this a good idea or not?”. One the one hand you can argue that since it’s not costing anything, then what’s the problem? Maybe Google Analytics does some things better than the system that you already have in place. On the other hand software like Google Analytics might be free to buy but it’s not free to implement (that takes time and effort) nor is it free to maintain (that takes time and effort too). Given that many organisations find it challenging to properly implement and configure one web analytics tool, does it make sense to try and manage two?

The other thing that struck me about this is that two systems will inevitably been giving different results. So which one do you believe? There’s a saying that a man with two watches can never tell the time. I can understand organisation wanting to try out different tools but at the end of the day I feel its best to stick with one and make sure that it’s giving you what you need.

There was some good news from this report about the adoption of other tools, particularly Voice of the Customer tools. Over 60% of organisations said that they looked at customer survey data. I think that if this survey had been done a couple of years ago the number would have been a lot lower. It’s good to see that businesses are beginning to realise that you can’t measure the effectiveness of the digital marketing strategy just by looking at data that comes out of a web analytics tools and that you need other data, particularly customer insight data to fully understand what is going on.

There are some worrying signs from the report. Organisations admit that they are still often not tying up their data collection strategy to their business objectives and relatively few said that they were definitely getting actionable insights from their web analytics. Quite a number thought that a lot of the data they had wasn’t particularly useful for decision making purposes and the clue to the reasons why came when you looked at the resourcing of their web analytics programme. 45% of respondents didn’t have a dedicated web analyst and when you look at where the money is being spent, the biggest chunk is usually on the technology rather than the resources to extract the value from the technology. So it’s hardly surprising that organisations are finding they are struggling to get insight from their web analytic programme that leads to better decision making.

The signs from the report suggest that there is progress being made in the UK but more vision is required at the right levels of organisations to tie their business strategy and the measurement strategy together. Reasons often cited as being a major barrier to having an effective online measurement strategy included lack of coordination, lack of senior level buy-in, budget and resources rather than problems with the technologies. And I think that if there is a difference between what is happening over here on this side of the Atlantic to what is happening in the US, it is probably more to do with those factors than anything else. For those of you in the UK and the rest of Europe, it’s worth taking a look at the report and seeing how you benchmark.

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

I have just finished attending the Emetrics Optimisation Summit in London. It has been a busy two days with a variety of presentations on different subjects from a variety of different organisations. I kicked off the conference by taking a look at the journey the organisations are on from web reporting to marketing optimisation and I took the opportunity to describe some of the necessary requirements along the way.

First of all there is the need to get the basics right. This means getting the right numbers right and having Key Performance Indicators that are aligned the business goals and that are strategic, action able, easy to understand and based on valid data. Once this has been done businesses can start to optimise their digital marketing processes but must ensure that they are organisationally ready to do this. I’ve talked before in this column about the need for organisations to have “the ability to execute”. There is no point generating all the insight required for optimisation if you can’t do anything about it. Finally there is the need for “customer centricity”, which means getting beyond the “one size fits all” approach to digital marketing and developing an understanding of your customer segments and the role that digital channels play within the relationship between them and your brand.

The comforting thing for me was to see some of the themes reinforced by other speakers from big brands in the UK and Europe. Julian Brewer from Barclays Bank talked about the journey they had been on from “Activity Counting” through to “Customer Intimacy” and how now they wanted to deploy their web analytics fare more operationally to move towards the concept of Customer Tailoring.

Dell talked about their Voice of Customer programme which not only included the organisational-wide deployment of a customer satisfaction tool but also the work that they are now beginning to do in monitoring and understanding the impact of social media and “Web 2.0″ activity on their brand. Angus Crombie from Dell explained why Dell felt they needed “better listening skills” and that comment reminded me that it’s not just about having the “Voice of the Customer” but actually listening to it. Another interesting aspect of the talk from Dell was the work that they had done to try and measure the impact that their Voice of the Customer programme had had on the business in terms of Return on Investment. Understanding and quantifying the ROI on the investment in measurement systems and analytics is a notoriously difficult thing to do. However Dell estimated that there had been a very short payback on the investments that they had made.

As at in San Francisco a couple of weeks ago, I took the opportunity to catch up on the latest thinking and discussions around the social media space. Listening to the various contributors in a panel session on the subject made me think that the discussions around social media analytics is sort of where the debate around web analytics was five years ago. There is a lot of discussion around the technology of data capture and reporting and the accuracy of measurement. There is also the obvious need to start to develop some standards in this particular part of the industry so that people know what these measurements are and how they are defined. I know this is something that the Web Analytics Association is beginning to address and it is definitely needed.

We also got an insight into how media companies are using analytics these days from Channel 4 on this side of the Atlantic and from the New York Times on the other. Channel 4 talked about some of the challenges involved in terms of tying up web metrics with business metrics. New York Times showed us some of the work that they have been doing in cross-channel analytics, tying up web data with circulation data and understanding the impact of online activity on circulations sales and vice-versa.

Perhaps one of the more interesting presentations was in the work that Econsultancy (www.econsultancy.com) had been doing to understand how to measure the effects of online PR. Having been saying that companies should be looking to measure the effects of their online PR activities, they decided to put their money where their mouth was and carry out their own study. They set up an online PR campaign and measured to the best of their ability the impact of that campaign in monetary terms. What was interesting was whilst they saw a positive ROI from the online PR campaign itself, there was also an additional benefit from improved search engine optimisation performance.

All in all, having been to two Emetrics conferences in the past few weeks (San Francisco and London), I can’t say that there was a massive difference between the two in terms of the issues being talked about and discussed. Core themes revolve around the need to move to a more analytical framework, to develop the tight kind of analytics “eco-system”, the fact thata we need to listen more and the challenges of social media measurement. The scale and the emphasis may be different but the main issues were the same.

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

As I write this I’m on my way back to the UK from the Emetrics Marketing Optimisation summit in San Francisco. After three days and having watched about 15 presentations this is probably the first chance I have had to reflect on what I’ve seen and what I have learned. The first thing that strikes me was the breadth of content that was covered. I went to presentations ranging from the “emetrics ecosystem” to usability and from testing and experimentation to social media measurement. The second thing that stuck me was the quality of the material and the presenters. In a show like this it’s possible to hit a duff presentation or two but looking back at my notes, all the sessions I attended were spot on.

So what did I take out of the conference? One theme that came through was there was a lot more evidence of organisations using integrated measurement strategies than I have seen before. More organisations were showing how they use a wide array of tools and techniques to understand the effectiveness of their digital marketing programmes. Voice of the Customer methodologies such as onsite feedback and surveys are the norm, most people are using testing and experimentation approaches and the use data mining and predictive analytical techniques is on the increase. Text mining tools are being used on verbatim comments from onsite surveys to extract the core essence of what is being said.

The stage was set on the first day with a keynote presentation “Competing with Analytics” from author Tom Davenport. There were some interesting things that Davenport said that set the tone for the conference. “The planets are aligned for analytics” he said, meaning that all the necessary components for organisations to adopt and deploy analytical capabilities are being put in place: Data, Enterprise, Leadership, Targets and Analysts. “Using analysis is good, competing on analysis is better” summed up the need to be able to move from insight to action. There is no point knowing stuff if you don’t do anything about it. He described the five stages of an organisations analytics capability from being “Analytical impaired” at the low end of the scale to being “Analytical competitors” at the other end. Organisations such as Harrahs and Marriott ion the US and Tesco in the UK use analytics as a source of competitive advantage.

Another stand out presentation was from Tim Goudie from The Coca Cola Company. Tim described Coke’s journey from the early implementation of their web analytics platform through to the development of their whole measurement framework. Goudie told us that “Metrics are ridiculously political; there is no such thing as a neutral metric”. Once you begin to measure things, then your are likely to start to change behaviour.

Other sessions I attended confirmed my belief that measuring and understanding the impact of social media is still in its infancy. Metrics and measurement frameworks are still in development, debates still stage about the meanings of terms like “engagement” and so on. Fellow columnist Jason Burby reminded us that when it comes to social media measurement of the importance of defining what success looks like in terms of key behaviours and that whilst the activities may be different the underlying measurement processes are the same.

A great take out from the presentation by Ebay was the use of “home visits” to better understand the user experience. I have seen this technique used by consumer packaged goods companies where people from the company visit consumers in their own homes to see them, using their products in real life. This was the first time that I had heard of this approached being used by an internet company. Executives from Ebay would visit users in their homes to understand the context within which the site is being used, revealing more insight into what really goes on than a standard usability test would.

Jacob Nielsen though showed what you can get out of usability testing in the laboratory. He asserts from the many tests they’ve completed over the years that task completion rates are going up and stressed the value of using testing early on in the development process. Oh and by the way “most people tend to ignore junk on websites”.

So this industry is now more than just what comes out of a web analytics tool. It’s about having a range of tools and technologies embedded within strong business processes. As Avinash Kaushik told us it’s about “multiplicity, flexibility and agility”. The planets are indeed aligned for analytics.

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

As you read this I will be getting myself ready to head over to San Francisco to take the pulse on the developments in the online marketing analytics world at the upcoming Emetrics Marketing Optimisation summit. For me it a great opportunity to take stock of developments in our industry as well as to catch up with colleagues and also friends that I have made at these events over the years. It will also give me a chance to compare how the US market is developing and compare that with developments over on my side of the Atlantic in the UK and the rest of Europe. There’s some debate at the moment about whether the European market is now sufficiently large and also sufficiently distinct to require its own professional body in the form of a European Web Analytics Association. My trip to San Francisco will help me in forming my own views for that discussion.

Looking at the programme for Emetrics in San Francisco next month gives some clues as to how the market is developing anyway. The size of the conference has increased since last time with more tracks covering more areas. This shows how the industry is broadening and, to some extent, fragmenting into a number of separate sub-disciplines such as campaign optimization, search analytics and so on. Also there is an increased depth to the conference with more sessions in some of the tracks. Last October in Washington I gave one of three presentations in the “Advanced Analytics Track”. This year in San Francisco I will be giving one of nine sessions in the same track.

Certainly when comparing the conferences in the US with the ones in Europe they are poles apart when it comes to scale. The summit in London this year (which I’m involved in) is shorter and has fewer tracks. But is this a reflection of the “sophistication” of the UK and European markets or is it just a reflection of scale? I suspect that it has more to do with scale than it does to do with sophistication. There are some really interesting things being done in Europe by some really interesting people. There just aren’t as many of them over here, particularly when you look at it on a market by market basis.

However, scale can be a driver of progress. For example, I observed this when the market for multi-variate testing and experimentation really began to take off in the US two to three years ago. It was easy for US companies to justify the investment in these services and technologies because they could see the returns. It’s taken the UK market until now to show the same growth in adoption. I think the main reason for that is the potential returns on investments weren’t there for many organisations because their online businesses weren’t big enough, not because they didn’t “get it”.

So it will be interesting to see whether what is talked about at Emetrics in San Francisco next week in the presentations and the lobby bar conversations is radically different to the conversations that I will be having in London two weeks later. And if they are different why is that? Is it because the market development is at different levels or is because the markets are just different. I think this will help inform the debate as to whether we need a radically different approach to developing and growing the industry over here.

It would be great to catch up with as many of you as possible if you’re travelling to San Francisco as well next week. Next time I’ll be writing this column on my way home and be giving my perspective on the conference. Till then…

This post originally appeared on Applied Insights’ blog. Foviance acquired Applied Insights in November 2008, with Neil Mason joining us as Director of Analytical Consulting. As part of this acquisition, we’ve incorporated Applied Insights’ blog into our own.

It’s been a year since we last blogged on the site and we have had the odd comment about it. At the back end of last year Avinash mentioned in his blog review of my presentation at Emetrics in Washington DC that we should have more content in our blog. As I explained to Avinash one of the challenges with a regular column at ClickZ that it’s not always easy to come up with sufficiently new and interesting stuff to talk about. And in any case there’s no way to compete with Avinash’s prolific output!

The web analytics space has many great bloggers, covering many different areas. Some are great on the technical side of explaining how to “do” web analytics, some cover industry developments and so on. I think it’s important to find some way to contribute to the debates without just adding to the noise. So, we’re going to give it another shot. We’re going to look at developments in the world of predictive analytics and data mining and I’m going to muse about digital marketing analytics and what’s happening here in Europe. We’ll be trying a few things out to see if they work, some will, some won’t, but that’s the name of the game. Stay tuned.

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

The classic digital marketing processes are acquisition, conversion and retention and so far in this series on digital marketing optimisation I have been looking at the components of successful optimisation strategies when it comes to acquiring traffic on the site and then converting it. In this final part of the series, it’s time to look at optimising retention marketing activity. My own definition of retention marketing is:

“Retention marketing is the art and science of converting someone twice without the pain and cost of acquiring them twice”

It’s not just about getting someone to buy again (or whatever the conversion action is) but using what you know about them to improve the chances of converting them again without having to go through the whole acquisition process again.

But somehow “retention optimisation” doesn’t quite sound right and I prefer to think of it in different terms. What we are trying to do once we have acquired a customer is to optimise their lifetime value and so I tend to think about this process as “customer optimisation”. How can I optimise the return on the investment that I have already made in acquiring that customer in the first place? What data, tool, technologies and processes do I need?

Classically we tend to think of email when it comes to retention marketing channels and used well it can be a powerful retention tool. However once you have transacted with a customer there are multiple touch points that can be used to increase the chances of them doing business with you again; the call centre, the store, the site etc and what is required is a view of the customer that straddles these multiple channels. This much easier said that done, especially for organisations with legacy systems that have been developed over the years. Often data on customers can sit in a number of disparate systems and it can take a huge data cleaning and integration effort to get the data into shape and fit for purpose.

So having good quality data is important but what you then do with it is pretty important as well. As I said earlier, what we are trying to do here is to increase the likelihood that the customer will transact with us again without the cost of repeated acquisition. What we want to improve is the “expected customer lifetime value”. The way to do that is to be in the right place at the right time by being relevant and timely.

Being relevant is about sending out the right kind of messages, whether it is in an email or on the site. Segmentation is a way of increasing relevance. Personalisation is a way of increasing relevance. These techniques, which may be manual or automated, are leveraging the insight that you have about someone to present them with more appropriate and relevant. These techniques do not necessarily have to be sophisticated to be effective, and in the early days of your customer optimisation programme being over elaborate can undermine the process. Remember, a key component of any optimisation programme is to have the ability to execute. That means that you need to ensure you have the processes and tools in place which allow you to act, measure and react.

For example, if you decide that you want to improve relevancy by having a segmented email marketing programme instead of having a single email that goes out every month then you’re probably on the right track. However, if your resources and processes are geared up around just sending out on version of one email every month, then it’s going to be a major step up to implement a segmented email marketing programme whereby different groups of customers will get different versions of different emails at possibly different times. You will need to have a more sophisticated email systems that can handle segmented email marketing programmes, your database will need to be more extensive and robust, you will need to invest in more copy and creative material and your processes will need to be more rigorous.

So it will pay to walk before you start to run and to look for the low hanging fruit. In terms of customer optimisation, I think that the most critical point is getting someone to make the second transaction. Generally there is a “friction curve” that needs to be managed. The steepest part of the curve is in the early days of your customer relationship. The more times that someone has transacted with you the more likely they are to do it again in the future; the friction isn’t as high. Getting them to repeat for the first time is the hardest part. So this is a special case in the programme and is when timing can be vitally important. The time when people are most likely to transact with you is just after they last transacted with you, so for this special group all about “recency”. The time to get them thinking about the next transaction is just after the first.

Ultimately profitable businesses are built on profitable customers and repeat customers tend to deliver the majority of the profit. Acquisition and conversion optimisation are essentially components of a success marketing programme but optimising long term customer value is key.