Optimisation using testing and experimentation technologies (such as Adobe Test and Target, Webtrends Optimize, or Google Website Optimizer) is mainstream for a lot of organisations. Companies such as Dell have built teams and processes to drive testing and experimentation through the business. Those companies have learned – and others are painfully discovering – that successful testing and experimentation is not only about implementing one of the many available technologies. It’s also about the need to harness people, resources, and processes around technology.

It’s similar to web analytics a few years ago. Back then, organisations implemented a system thinking that it would solve their measurement problems but then realised they needed analysts. Likewise, organisations must build structures and processes around testing and experimentation technologies, otherwise the business will not extract the potential from the system.

Testing and experimentation involves a lot of moving parts. Tests must be designed, assets created, technologies configured, and results analysed. Successful testing and experimentation programs require strong project and program management capabilities. Larger organisations typically have dedicated resources for program management, whereas in smaller businesses it might be part of someone’s role. In either case, a central function must identify which tests are planned and then manage them through the system. Workflows must be created to ensure that the assets to be tested are created and deployed onto the system at the right time. Tests must be monitored to ensure that any variants that are adversely impacting the experience can be dealt with.

Two Places Where Right-Brained Creatives Can Assist With Testing

All of this is predominately “left-brain” activity, i.e., managing, coordinating, analysing, testing, and experimenting also needs “right-brain” input, a more qualitative approach incorporating a user experience perspective. This right-brain input is important into two areas:

• Test program development (what to test)
• Test design (how to test)

Test programs are often built on the basis of web analytics reports showing which parts of the site might have problems. An additional input into the test program can come from understanding what’s working and what’s not working from the user experience perspective. The main sources of insight are from voice-of-the-customer survey programs and user experience testing. Many organisations have ongoing survey programs and many elicit user feedback through open-ended questions such as “How else can we improve the site?” User feedback can be a rich source of insight, but it must be mined, contextualised, and interpreted. These are right-brain attributes. This qualitative input helps to define what are the important areas of the site to improve and where to direct testing.

Second, right-brain input is needed for test design. Once a test area has been decided, the next issue is to decide what different elements will be tested. In a test, there will always be a winner even if it’s the existing version. With testing and experimentation technologies, you can cycle through many different combinations until there’s a significant improvement. But the challenge is how do you know that the variants that you’ve decided to test are the best ones? How do you know that the winner is not the best of a mediocre bunch? Optimisation specialists may know that certain things tend to work from the body of tests they’ve seen, but other inputs such as user experience expertise help to improve the quality of testing.

Good testing and experimentation is a combination of art and science, rational approaches and intuitive perspectives, and left-brain and right-brain inputs. It’s time to take a whole-brain approach to testing and experimentation.

This article was originally published by ClickZ

Fragmentation, optimisation and integration. Those were the themes that stood out for me at last week’s Emetrics Marketing Optimization Summit in Washington DC. First of all I was reminded that “web analytics” is not was it used to be, it’s an increasingly complex space. Secondly, I was shown some great evidence about what’s really required to be an optimisation orientated organisation and finally we’re beginning to see some case studies from organisations that have made the investment in multi-channel data and the benefits they’re accruing from that.

A strong theme from the conference was the search to understand the value of social media. I got the impression that, if you were a speaker on track then you were in trouble if someone else had the words “social media” in the title of their presentation. Social media analytics is now definitely part of the landscape but its’ hard to define what it really is. Everybody is coming at social media from a somewhat different angle; online brand reputation management, fostering innovation or customer service, so it’s inevitable there is a disparity of thinking about how to measure its impact. So it was useful to see people like John Lovett from Web Analytics Demystified talking about the framework that have put out there with Altimeter. I think Lovett would agree that the framework itself is not rocket science as it’s essentially about linking metrics back to objectives but I think it’s exactly what’s needed at the moment in the space at the moment to take some of the “mystery” and “fluff” out of social media analytics. As one of my colleagues would say “at the end of the day, it’s just data”.

Optimisation has been another hot topic for a number of years now. Before we used to be treated to presentations that espoused the benefits of using approaches like A/B and multi-variate testing and the kinds of uplifts that could be achieved. What we saw this time from the likes of Dell and eBay was what’s actually required from an organisational and technological perspective to actually implement an optimisation culture in a business. Ed Wu and the team from Dell demonstrated the size and scale of the investment that’s required. They doubled the size of the testing team, bringing on an additional 10 hires in a 2 month period. They described the challenge in finding enough of the right kind of talent. In addition they established a project management office to help facilitate the execution of tests and introduced project management tools to manage the whole process. The Dell story just underlined that analytical success is as much, if not more, about people and processes than it is about technology.

That’s not to say that technology isn’t important and Bob Page from eBay outlined the type of investment that they’ve been making in getting their data architecture right to support the various analyst communities in the business. Initiatives included getting rid of the various datamarts that had sprung up around the company and creating centralised virtual datamarts that were able to flex and meet the shifting demands of different analytical groups across the course of the day. Technology is also used to connect different analytical groups together. A networking site joins together the various analytic communities together where initiatives can be shared, knowledge can be captured and best practices can be developed.

Finally, we began to see some of the benefits that accrue from data integration strategies. Adam Greco from Salesfroce.com outlined how web analytics data and CRM data can be used together to improve the effectiveness of the lead generation process. Lead data given to sales people can be enhanced with not just what’s on the contact form but also with the prospects previous browsing behaviour on the site, highlighting the products and services that the prospect might be interested in and scoring them in term of their levels of interest and stage in the sales cycle.

This type of data integration requires planning and for data from different sources to be matched together. Allen Crane from USAA showed how they had been doing this integration across multiple channels. Over a two year period they have been bringing data from the different channel into their centralised warehouse and analytics tool. They created a data schema that focussed around the customer and built out around that. In what I think was probably one of the best case studies around multi-channel data integration I have seen in a conference, Crane showed how they had developed the notion of a “conversation” to encapsulate the interactions between USAA and a member across multiple channels around a single event like taking out a personal loan. That conversation might start online but end up offline, or indeed end up online again. Their data integration allows them to track these conversations and to understand the true costs associated against these different events. It allowed them to develop new metrics like ‘containment rate’ (the amount of the conversations that happen online) that enables them to prioritise their site and channel optimisation efforts. For me this is where web analytics is heading. It’s about taking that data, adding the multi-channel perspective, and then deploying the right people and processes to change the way the business does things.

Foviance’s Neil Mason, Director of Analytical Consulting will attend again this year as a guest speaker.

I’m increasingly convinced that the issues that most businesses face around the successful deployment of analytics in their business are not to do with their technologies but to do with their businesses processes. That view was reinforced this week when I was running a workshop with a group of students studying on a Masters Programme in Internet Retailing.

As part of the session I asked the class what they thought some of the key ingredients were in executing successful internet optimisation. They started off by throwing out items like “good data”, and “technology”, and then moved on with things like “flexibility”, “willingness to fail”, “good hypotheses”, “risk culture” and “strong business model”. I then asked the class how many of them worked in organisations that had those characteristics. No hands went up.

Often organisations are happy to spend money on new campaigns or large scale product development on their site without thinking or being explicitly clear about how they are going to measure the effectiveness of the campaign or the new piece of functionality. So how do they know that they have done a good job? The measurement piece also needs to be built into the campaign or product development process as well. Here is a simple framework to use as part of that process.

• State the objectives
• Define the success indicators or KPIs
• Perform a gap analysis
• Create the measurement roadmap

State the objectives

Before you start, be very clear about what you are trying to achieve. State your objectives and make sure that they are not what I call “marshmallow objectives”. Marshmallow objectives are ones that are soft and squidgy. They are not firm and they don’t hold up to scrutiny. These objectives are difficult to measure. People often talk about making objectives “SMART Objectives”. SMART objectives are Specific, Measurable, Achievable, Realistic and Time bound. You should try and make your objectives as SMART as possible. If you come up with objectives like “to improve the user experience”, force yourself to be Smarter and ask yourself questions like: “why?”, “which users?”, “in what way?”, “by when?”

Define the success indicators or KPIs

Next define the measures of success or the Key Performance Indicators. These should relate directly back to the objectives. If the objectives are SMART then the definition of the success metrics should be relatively straight forward. Constantly ask yourself “What does good look like?”. If your are achieving your objectives, what will be happening in the business or on your site? Sometimes it can be difficult to measure objectives directly with significant cost (see below) then you may need to come up with other success metrics that are indirect measures of success.

Perform a gap analysis

Once you know what it is you want to measure, perform and analysis of what you can measure now versus what it is that you ideally want to measure. Where are the gaps? Do you have the right measurements systems in place already and are they configured the right way? For example, f you want to improve likelihood of someone booking a holiday once they have done the research on the site, you might set up a success metrics that is something about visitors propensity to book at a later date. You may need a survey in place to be able to measure one. So do you need to set up a survey from scratch or do you just need to ask a specific question on an existing Voice of the Customer programme?

Create the measurement roadmap

The final stage is to create the measurement roadmap. This is effectively the plan of how you are going to measure the things that you need to measure, or as I like to say, “Count the things that count”. A key part of this is prioritising the work that needs to be done, being clear which gaps you are going to plug in your measurement systems and then how that work is going to get done. This could range from just ensuring that there is a specific custom report developed through to the implementation of a new piece of software or the adoption of a new service.

The process I have outlined can take days to complete or it might just take a matter of minutes. It might be a very strategic piece of work looking at the business overall or it might be quite tactical, for example running an A/B test on a landing page. Whichever it is, it’s a way of putting measurement and analytics at the heart of your business processes. So anytime you’re planning to do something, ask yourself (or your colleagues): What does good look like? How will we know we’ve done a good job?

In short, no, it’s not but this question regularly comes up. I recently discussed this issue with our User Experience consulants and got some consistent responses:

“Keep it as one field per line. People will be able to use the forms more easily by having one flow rather than having to read across and down. I would have thought there would be a higher instance of people missing fields with two or more rows.”

“Not only will having two drop-downs on one line look more cluttered/complicated etc, but it will be less efficient as users will have to go left to right as well as down the form.”

“A long vertical list is better as it maintains focus and reduces error rate. No official stats, but just my observations from previous testing.”

This confirmed my recommendation: Keep one field (e.g. text fields, dropdown menus) per line and think of reducing the fields on the page instead. If the form is really too long and all the fields are necessary (and most of the time they are not) the form should be split in two and have a Step 1 and Step 2.

From an accessibility point of view two dropdown menus next to each other do not violate the DDA guidelines, however, it will make the form more difficult to read.

I hope this proves useful the next time you review the layout of an online form.

There is a generally accepted view that an organisation’s multi-channel customers are its best customers. The theory is that if a customer buys from an organisation over more than one channel, for example in the store, from a catalogue and over the web, then they are more likely to be of higher value than if they just purchase through one or two channels. I can see there is a natural inclination to believe that if a customer does business with an organisation over more than one channel that it is probable that the customer has a higher degree of loyalty and hence value. However, the mathematics of the analysis state that a multi-channel customer is also more likely to be of higher value anyway by the simple virtue of having bought more than once rather than necessarily because they bought across different channels. So understanding the value of multi-channel strategies requires a bit more careful consideration than simply looking at the average customer value.

There is another dimension I think as well to evaluating the impact of multi-channels strategies. In the example above the focus is on the result and the channel in which the transaction occurred. From a customer perspective that is fine but to fully understand how multi-channel strategies are working (or not) it’s also important to understand the dynamics between the channel that the customer was acquired in and the channel in which the transaction takes place. This is particularly important for understanding the role of the online channel in driving offline transactions and there are two important ingredients to achieving this. The first important thing is to have the tracking mechanisms in place to be able see multi-channel behaviour. I admit this can be easier said than done. The second important thing is to understand why multi-channel behaviours are happening the way that they are and then to evaluate whether some of these behaviours are desirable or not.

The type of industry an organisation is in and the type of channels it uses to do business will determine the appropriate methods it can use to track multi-channel behaviour. For example, the use of a specific telephone number on the website for the call centre or using source codes or reference numbers to identify customers. Some of these methods will be more accurate and reliable than others but the initial solution to understanding the multi-channel puzzle is to have at least some mechanisms in place to track behaviours.

The next issue is then to understand the behaviours that are being tracked. It’s likely that first challenge will be to integrate the data from the different channels. Data may need to come from web analytics systems, call centre systems, customer databases and so on. Data will need to be cleaned, integrated and then analysed. This may require some different data analysis tools. The type of analysis you need to do will depend on the type of problem you are trying to solve. Let me give you an example based upon work we have done in the travel industry.

A company sells holidays to an older target market. The main channel historically has been telephone sales through a call centre though the web channel now makes up a significant proportion of their business. The website also allows visitors to download a brochure and it also gives the number for the call centre. Although web site traffic is growing steadily, the conversion rate was not increasing. Increased sales were a function of increased traffic.

The company wanted to increase the conversion rate to get more bookings transacted online as opposed to through the more costly call centre.

The website already had its own special number for the call centre so the number of calls that originated online could be tracked. The next stage was to understand how many of these calls turned into bookings. In this instance the call centre system didn’t allow bookings to be tracked against specific inbound numbers, so for a period of time call centre operatives receiving “web calls” were asked to track how many of them resulted in a sale. In this way a conversion rate could be calculated.

The other aspect was to understand what happened when people ordered a brochure from the website. The approach here was to match the names and addresses of people who had ordered the brochure online and to cross-reference them against bookings received in subsequent months and to look at what channel they had booked through. Although perhaps not perfect it seemed to be good enough. From this analysis we could determine how many of those people who had ordered a brochure online had subsequently booked and which channel they had used to make the booking (via the call centre or via the website).

This analysis allowed us to do two things. First of all we were able to estimate the total value being delivered to the organisation. This was not just the value of the online bookings but also the value of the bookings that came through to the call centre on the special website number and even those who had ordered a brochure from the website and had subsequently booked via the normal call centre number. In this case a significant proportion of the internet channel’s total value to the organisation came from its delivery of business into the offline channels and highlighted that the way that the organisation had been historically measuring the value had been underestimating the true Return on Investment.

The second thing that the analysis allowed us to do was to explore the dynamics of the interaction between the online and offline channels and to understand why some of these behaviours were happening. I’ll go into that in more detail next time. Till then…

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 post originally appeared in Applied Insights’ events section. 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’ events list into our own.

This year Neil was invited by Jim Sterne to be the conference chairman and a keynote speaker the Emetrics Marketing Optimisation Summit in London.

As well as fronting up the proceedings over the two days and trying to keep the conference (and its speakers) on track, Neil delivered a keynote presentation looking at the development of web analytics and marketing optimisation practices within organisations called: “To Marketing Optimisation and Beyond!”

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.

Last time in this series on digital marketing optimisation I looked at the process of campaign optimisation. But as the saying goes: “You can lead the horse to water, but you can’t make it drink”. Whilst your efforts make people aware of your brand and to give them a compelling reason to visit might be fully tuned, it’s what happens when they get to the site that makes the difference between online success and failure. So today, let’s take a look at conversion optimisation.

To start of let’s be clear about what we mean by conversion optimisation. To be more precise what do we mean by conversion? To optimise effectively you need to optimise some defined outcome and it’s important to clear about what the desired outcome is. For example, if you have a site where people can either complete the transaction online or pick up the phone and call the call centre, which one of those outcomes do you want to optimise? It may not be possible to optimise both. If you optimise the site to increase the online bookings you may find that the process doesn’t work for those people who prefer to research online but transact over the phone. If you optimise the site to generate call centre volume, it may mean that you have to incur extra costs in the call centre to deal with the extra demand. So, clarity of purpose is an important ingredient in the conversion optimisation process.

The conversion process is not one process; it’s a series of mini-conversion processes. Each of these processes needs to be optimised. You need to chunk the problem into bits. What is right for you will depend on your site and what you are trying to achieve. Fairly generically, the main micro-processes are: Land, Browse/Search, Engage/Transact. Part of the analytical approach to conversion optimisation is to identify where it hurts most. Which part of the conversion process seems to be causing the most problems? However, this also has to be balanced against the “ability to execute”. Which parts of the website can you change or impact in which timescales? It may be that the checkout process is identified as requiring optimisation and tuning but it may be that it will take 3 months before you can get the development resource to make the changes. In the meantime you be able to change some other parts of the site more tactically.

In an ideal world it would be great it is was possible to make changes to all parts of the site with relative ease and to measure the changes to get to the optimal result. There are technologies and platforms out there that are making this easier to do but in many cases the reality is that real choices need to be made in terms of impact versus time to effect. In these cases my instinct is usually to start at the beginning and look at landing page optimisation. Landing page optimisation is something that increasingly is becoming easier to do and it’s an area where there is always the potential of a high impact.

For me one of the biggest challenges in digital marketing is getting someone to do something twice. A lot of people who visit a website only visit it once, they only look at one page, and they stay for less than a minute. If they buy or transact, they only do it once. So how do you get them to do it twice? Look at that second page? Stay for that second minute? Make that second visit? A lot of subsequent behaviour is determined by the user experience on the first page of the first visit. The first page of the first visit needs to generate the momentum that ultimately leads to a successful outcome.

The growth of testing and experiment systems such as those provided by brands such as Optimost and Offermatica have made page optimisation processes a lot easier. They enable some of the hurdles associated with enacting change to be overcome and provide a systematic way to understand how to improve con version. They are not the only tool in the toolbox and conversion optimisation is an area where a wide array of data and services can be used in a holistic way to understand and optimise the user experience. Good site analytics gives an insight into the effectiveness of the micro-conversion processes, surveys help you understand the level of satisfaction with the user experience and usability testing tells you (warts and all) what processes works, which ones don’t and why.

Having gone through the process of acquiring prospects and converting them into customers, do you want to go through the pain and cost of doing it all again? I thought not. Next time we’ll take a look at the process of managing your investments in acquisition and conversion through optimising your retention marketing processes.

Till then…