Analytics Strategy

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

Maturity models seem to be all the rage these days. These models help organisations to identify where they are on the roadmap of whatever discipline or capability the model is about and where they need to be. They help to describe the journey to world-class status or best practice. I have been using a simple “maturity model“ for a few years to help organisations identify where they are in terms of their development of their digital marketing optimisation capabilities. I’ve found it a useful device to help people understand the journey they are on and a sense of the ultimate destination. Read more…

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

In my last article I looked at the measurement aspects of understanding multi-channel dynamics. This week I’m going to look at some of the analytical approaches. Having put in place the mechanisms to track cross-channel behaviour, it’s important to explore the observed dynamics of the interaction between the online and offline channels and to understand why some of these behaviours are happening and whether they are desirable or not.

A point of focus for an organisation might be to understand why a customer who starts a transaction online then ends up completing it offline. Many organisations would usually prefer those transaction to be completed online as its cheaper to process the transaction. The reasons why this channel shift occurs could be down to the way that an organisation does business, down to traits of consumer behaviour or because of the complexities of the product.

A while back we worked with a bank to map out the channel dynamics and to try and measure the channel shift from online to offline. This was complicated by the fact that the bank had installed internet terminals into its branches to allow prospective customers to fill in applications for some of the simpler products online but in the branch. The idea was that it would reduce the need for customers to wait until branch personnel were available and that one branch person could help many customers at the same time. Branch personnel would also be freed up to sell more complex and higher value products. However, what the bank found was that the branch personnel would often lure people away from the branch terminals to do the transaction on their own systems. The reason was simple and that was the branch personnel didn’t get commissioned on sales that were made on the terminals in their branches. In order to get the desired behaviour the bank needed to capture the IP addresses of the terminals in the branches, link them to the sales made on the terminals and then allocate those sales back to the branches. In that way the branch personnel were much happier about allowing people to “self serve” in the branch.

Last time I talked about a holiday company serving an older target market. Having set up the measurement tracking capability to look at cross channel behaviour, we set about analysing why channel shift as happening. We looked at the bookings that had been made on the website and compared them against bookings where someone started the process online and then had completed the process in the call centre. Across of the things that we looked at the gender of the person making the booking was the biggest factor. Men were more likely to do their research on the internet and book online. Even if they had ordered a brochure they were more likely to go back online to make the actual booking rather than call the call centre. Women on the other hand we4re far more likely to use the site for research only and to order the brochure but would then call the call centre to make the actual booking. Focus groups confirmed that this was the preferred apporach for women and so in this case channel shift was down to gender differences.

In some cases channel shift might be down to website issues. We conducted a similar piece of analysis for an insurance company looking at channel dynamics on their car insurance products. Once again we assembled the data to look at the bookings that were made online and compared them to those bookings that end up in the call centre. We looked at a number of different characteristics including the type of insurance cover, the car being insured as well as the demographics of the policy holder. In this instance given the breadth of the data we used Chaid analysis to identify those characteristics which were the most important in predicting channel shift. The results were somewhat surprising. Rather than demographics being the most influential factor as I had had suspected, it was actually whether someone had bought a particular optional extra on the policy. If they had, they were far more likely to have completed the transaction in the call centre. Armed with this information, the company went back and reviewed the site processes for buying this particular optional extra on the policy and could see where the process could be improved to help reduce the need for people to call the call centre.

Channel shift may be down to organisational issues or site issues. These issues can be addressed. Other factors may be more ingrained in the way that customers want to do business and so in these cases channel shifting should be embraced as long as it’s recognised accordingly.

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

Here in the UK recent statistics have confirmed that the economy has stopped expanding and that it’s possible that we may head into recession. We have had continuous economic growth for the last 16 years or so and so for many people operating in a recessionary environment is going to be new. If it’s like the last recession we had in 1991/1992 then it could be tough. So, when it comes to marketing there’s probably two ways that organisations and businesses might react.

The dumb way to react will be to slash sales and marketing costs across the board, batten down the hatches and hope to ride out the storm. Marketing services costs like investments in measurement, analytics and research will be some of the first causalities as they are seen as “discretionary” costs and not core to the business operations. Also each channel or division will take a similar hit.

The smart way to react will also be to reduce sales and marketing costs. After all, if you are selling less, you have to react accordingly to maintain profitability. However, the smart organisation will look at how they can significantly increase the efficiency and effectiveness of their marketing expenditure and what are the important activities and tools they need to be able to do that.

In a recessionary environment it may be that the online channel is a winner. Smart organisations will look to see how they can acquire or service customers more cheaply through the e-channel than through other channels. Even with the digital channels, I believe the marketing emphasis is likely to shift with three possible trends:

• An increased focus on multi-channel acquisition optimisation
• Greater deployment of conversion optimisation tools and applications
• Development of more robust and sophisticated retention marketing programmes

As acquisition budgets come under pressure, digital marketers will need to focus on how they get more bang for their buck. Classic single channel optimisation techniques such as PPC bid optimisation will only work to a certain extent as all organisations will be looking to improve channel productivity. However single channel optimisation will essentially remain sub-optimal. Smart organisations will allow investment into the tools and analytics necessary to understand how to optimise budgets across digital acquisition channels such as display, affiliates and PPC. They will ensure that they have improved attribution models that enable them to understand how channels work alongside each other (or not) and which channels are delivering value. They will also ensure that they are able to reduce the costs of Cost Per Acquisition (CPA) programmes not only through better channel optimisation but also through correct attribution of sales or conversions to the correct channel. To do this, organisations will need to look at how they collect, manage and analyse their campaign related data. Joined up marketing is difficult to achieve without joined up data. They will also need to have the right tools and skills sets to allow them to analyse that data to understand that data. Improved effectiveness will come from improved analytics.

Having persuaded someone to visit the website, the trick is to get them to do something of value. Conversion optimisation has come of age in the past couple of years but is still a nascent practice in many organisations. To leverage the investments in acquisition, organisations will need to ensure that conversion rates increase. Site designs need to continue to improve and the customer experience enhanced. To do this will require a greater understanding of what’s working and what isn’t. Good site tracking will be vital not optional. Also testing and experimental tools as well as behavioural targeting platforms can be viewed as investments that have a measurable ROI. Therefore despite a potential squeeze on budgets these types of capabilities can pay for themselves inj a relatively short period of time if they are deployed correctly. Organisations should look to improve the effectiveness and efficiency of their processes and procedures around the tools to save money rather than reduce the investments in the tools themselves.

Finally, the other trend will be the development of more robust and accountable retention marketing programmes. I often think of the digital world as a “world of ones”. Most people who visit your website only ever visit it once. A lot of them only ever look at one page or stay for one minute. If they convert, they only do that once. Most of the challenge in digital marketing seems to be to get people to do something twice. Visit twice; make the second click; place the second order and so on.

The classic saying is that it’s far cheaper to retain a customer than to acquire a new one. In recessionary times it makes sense then to focus on extracting more value from the investments already make in customer acquisition and conversion than spending more on the same. For me the definition of retention marketing is the process of converting someone twice or more without paying the costs of acquisition and conversion twice. At the point of initial conversion there is usually an exchange of value. You sell them something; they tell you their name and address. They download something, you get their email address. You also know what they bought or downloaded and so that insight forms the basis of improving their propensity to transact with you again with relevant communication at the right time. Using tools and techniques such as segmentation and predictive analytics will help with both relevancy and timeliness.

If there are stormy waters ahead what are you going to do? Batten down the hatches and hope for the best? Or invest in the right navigation equipment, learn how to use it and plot the smoothest possible course to keep ahead of the pack?

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

A couple of weeks ago I met up with executives from Omniture here in the UK to get a bit of an update on the products and the product roadmap. After all the acquisition activity over the past 18 months and the subsequent integration of the various operations, a number of product launches and the rebranding of some of the businesses, it was useful to get a perspective of the Omniture business as it stands and where it’s headed.

After having talked for a couple of hours it seemed to me that Omniture have got most of the bases covered. SiteCatalyst offers core web reporting and analysis capabilities and data integration requirements are managed through the Genesis programme with dozens of partners covering most digital marketing disciplines. Optimisation capabilities are offered through the integration of the Offermatica and Touch Clarity into the “Test and Target” service. High end analytical requirements are covered by the Discover product including the Visual Sciences product rebranded as Discover onPremise. And at last we see one of the benefits of the Instadia acquisition through the launch of Omniture Survey which allows survey response data to be integrated with web analytics data.

Having been through a number of company and product integrations in the past in the marketing services industry, I understand the challenges involved in bringing together a mishmash of different services and cultures into something that looks like a coherent product line up. From what I have seen I think Omniture have done a pretty good job. The presentation of the services makes sense and you can see how they can deliver against an organisation’s needs as they evolve and grow.

This is not meant to be an ad for Omniture but I did come away from that meeting thinking that if Omniture can be used as a proxy for the web analytics industry then the industry is at an interesting point in its development. Over the past couple of years a number of the vendors have broadened from the core application of web reporting, either through acquisition (as in the case of Omniture) or by being acquired themselves (as in the case of NetTracker). The question is: where next? Will web analytic tools develop into enterprise level systems capable of supporting multi-channel analytics or will they remain a “point application” for the digital marketing channel?

The model for hosted web analytic systems is that everything is fine if you want to analyse and manipulate the data within the system itself. Generally the tools are getting better at analysing and reporting web data and the systems are getting easier to use. The challenge comes when you want to either report or analyse the data in a different way or even using a different tool. Let’s take an example.

Everyone knows that the “last click” attribution model for measuring campaigns is naïve. Advertisers want to understand better the relationships between different digital channels and their impact on an eventual conversion. The standard model in most tools is to use the last click with an option of using the first click to allocate a conversion to a channel. In some cases you can also allocate the conversion equally across all channels involved. If the advertiser wants to look at different ways of attributing conversion to marketing channels in a typical hosted environment then they would need to get the data out and analyse it separately. This then presents another challenge.

Hosted web analytics systems generally offer an “all or nothing” approach when it comes to exporting the data. You can export the topline reports into Excel or similar and that’s it, or you can also have all the raw clickstream data. It’s like saying you can have the drips from the tap or you can stand in front of the hose and get soaked. Few organisations are equipped to handle raw clickstream data which is why they opt for a hosted service in the first place. There is too much noise in the data and part of the value of a web analytics system is that it manages and processes the data into something that is analysable and reportable. But in the process sometimes it dampens the noise too much so that it’s hard to see what’s going on. The example of the campaign attribution is one example.

What organisations increasingly need from their web analytics systems is the ability to have access to clean, summarised but granular data. WebTrends have made progress in this direction with the Visitor History File. It allows you to export on a regular basis a series of attributes against each visitor that comes to the website. It includes for example the first campaign that attracted the visitor, the last campaign, the total number of visits and so on. It doesn’t solve all the problems but it is a step in the right direction. Increasingly organisations will be looking for tools that allow them to integrate the data more easily into other marketing or corporate systems so that they can understand all the customer touch points. It will be interesting to see how the industry responds. Will it see itself as a solution for digital marketing only or will it be an important component of the broader mix?

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.