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How to build a world class online conversion department

Any smart online company should have one. I am talking about a conversion department. Unfortunately not many companies have realized the potential in optimizing the online traffic. The few companies that do i.e. Amazon or Expedia have a rumour to have the highest conversion rates within their field. These companies understand the potential of working systematically with optimisation since even small changes can yield great results. I am a first-hand witness that simple actions can yield a double-digit conversion increase.

Why you should have a conversion department

Successful online companies have analytics built in into their DNA but that is not enough. Analytics data is useless if you don’t use it to increase your revenue. Many companies have more data than they can handle but have a hard time leveraging this data into revenues. This is where a conversion department will come in hand.

The aim with a conversion department

The main task of a conversion department should of course be to increase your online conversion and hence your revenues but it should also make your organisation smarter by leading the optimisation of all your digital channels.

Further a conversion department should centralize all conversion knowledge, gather it in one place to ensure that the knowledge does not disappear when people leave the organisation. If you are a large organisation with offices all over the world it should also have the aim to overview the optimisation process save time by avoiding that the same mistakes are being done over and over again.

The conversion department together with the analytics department should also be the cure to the HIPPO (Highest Paid Persons Opinion) sickness many companies have. The HIPPO sickness is when decisions are based on emotions rather than facts. This will create a culture based on facts not guessing.

What a conversion department does

Many think that a conversion department just do AB testing. AB testing is a very important part of the tools conversion people at their hand but it is just a small part of the benefits your organisation can have. Here are some other benefits:

  • The conversion department bridges the gap between, design, analytics, marketing and technology. They give your analytics guys the understanding of what needs to be focused on and they give your marketing people the knowledge of what works and how to invest their money in a smart way. Further you designers will start thinking conversion, which will increase the quality in their output.
  • Your organisation is most likely already measuring everything. You have brilliant people getting you all data you need. You have more data than you can handle but you have hard time capitalizing on this data.
  • People working with analytics are good with numbers but not with online sales. Online sales are much more than just understanding numbers therefore you need people understanding the dynamic of how to sell online.
  • With marketing people it is the opposite, they might be good in sales ideas but they lack the discipline of numbers. Many times they also want to ignore numbers and to be able to some “branding”. Brilliant sales people understand the psychology involved in selling especially when you sell to consumers but still need the support of conversion professionals.

The building blocks

Building a successful conversion department demands more or less the same components as any other department you will build. Money, passionate people, structure and key competence.

  • First of all you need passionate people. People that love the online world, people who are prepared to be persistent creating your cutting edge conversion department.
  • You will also need people with analytics skills.  Since you will do a lot of ab-testing you need to understand what to test, which demands knowledge in web analytics.
  • Tools are a key part of any online business. Online conversion is no exception. Fortunately the tools now days are rather cheap so you can get really good tools for a fair amount of dollars. Usually it is not getting the tools that are the problem but rather learning how to use them that are the crucial part.
  • Without a budget your conversion department will be limping. You need to allocate enough resources so you will be able to have a cutting edge department. Today companies allocate 99% on traffic driving and only 1% on optimizing this traffic, which is of course ridiculous. Getting the traffic is more expensive than squeezing the conversion juice out of it.
  • Since the department will be doing a lot of cutting edge conversion work you need people that can convey the results in an inspiring way. Good presentation skills are a must and keeping a good documentation of all the knowledge you will generate is another important factor.
  • Keep in mind that before you build your conversion department you need to have clean analytics data. Your data must be correctly implemented data and if you have a BI department don’t hesitate to take their help.

To think of

As a final word when working with important projects like this you need to consider that there are many stakeholders within a company and you need some political sensitivity, of course without giving up your conviction that facts speak louder than words. Also you need to be prepared to be in for the long run. Transforming towards a conversion culture takes time but worth it many times over. You want to be a cutting edge online company, don’t you?

The secret conversion formula that will boost your online sales

There is a tightly guarded secrete in the online world. I am talking about the online sales formula. With this formula you can reach a double-digit conversion increase everyone talks about.

Trying to search for “online sales formula” will generate slim results. Fortunately I have been working with the formula for years and I am prepared to “reveal” it.  The first time I got in contact with it was a few years ago. I had changed workplace and my new colleagues told me about this course they had went on where they had learned how to use this new and fresh conversion formula. We applied it to our optimization work and it generated great results. Eventually our designers, various stakeholders, editors and others started to apply their work with the thinking of  the conversion optimisation formula.


The revised conversion formula

Fast forward to present days, I have moved on and applied my knowledge on my new work. Working with a different business model I have noticed that the conversion formula has two flaws. Or more correctly it is missing two big factors that can affect your conversion rates substantially. Those two factors are the brand value and the social media effect.

Now let us look at the revised online conversion formula and its different parts.

Conversion = (4M + 2B) + 3V + 2(I-F) + 1S – 2A

  • M = Motivation. What is the motivation of the user? Where in the buying process is he? Is he the instant decision type or is he more on research mode?
  • New! B = Brand. Well know brands have a higher conversion. This has a lot to do with trust, since brands communicate value, security, credibility etc.
  • V = Value proposition. How high is the value of your offering? Manipulate this and you will affect your conversion rate greatly.
  • I = Incentive to buy. This could be different type such as limited time only.
  • F = Friction. What type of friction does for example your landing page have? Conflicting messages? Vital information that is missing to take a decision?
  • New! S = Social media, how much is your brand talked about. There are some really successful cases where you can use social media to sell directly or indirectly. Notice that if you can also have a negative social media buzz which will lower your conversion rate.
  • A = Anxiety. What will you do with my credit card details?

I am not going to explain in detail how to use this formula, but you need to do some hands on work in a step-by-step manner. You need to do a lot of ab-testing focusing on various parts of your channels, your message, your landing page and your marketing mix. Eventually this will reveal how big the various factors are for your business. When you have reached this stage you will be able to manipulate these factors and maximize your bottom line revenue.


The optimisation results

At my current work I we have been working especially with the value proposition (V). By manipulating this value we have managed to increase our conversion rate up to 300%.

Based on the formula let me share some success cases I have worked on.

  1. V = messing with the value we offered increased our conversion by 300%. When increasing the amount of a voucher offered together with a purchase from 300 to 500 sek we saw and increase in the sales by +110%. When increasing this amount to 1000 sek we managed to increase the conversion by +300%.
  2. B = doing a lot of TV and print commercial allows us to sell more with less hustle. For example we can see a direct correlation of our online sales and the print send-out. The days the print lands in the mailboxes we double our sales. Also we have an extremely high volume of brand search, which brings in high quality traffic.
  3. M = targeting keywords that are close to the end of the buying process increased our conversion with up to +400% compared to long tail keywords.
  4. S = increasing our likes by +700% (from low levels though) generate direct revenues from this channel whenever we promote our offer. The offer is being promoted among our followers creating an exponential reach of potential customers.
  5. A = when displaying a secure shopping by VeriSign in the first page but not on the consecutive pages in the buying processes we increased conversion by +12%.
  6. F = we always remove the site navigation bar on the landing pages and this increases the conversion as much as 15%.

Optimizing the channels for the highest online sale conversion is a crucial part of any online business. I think this formula will give you the correct framework to create a systematic hands on approach to optimisation.

The formula also cuts through the clutter of factors many people claim have an effect on your conversion. If you manage to apply it correctly to your channels you will increase sales most likely by double digits. To be honest, getting there is harder than it sounds, you will need resources, a smart organisation, time, a bit of creativity, some knowledge and of course the blessing from top management.

If you have tried this formula do not hesitate to tell me your views in the comment fields below.

All web analysts will soon be fired

I think technology is an amazing phenomenon. It is so amazing it will eventually replace your job as a web analyst.

As a society we develop through technology. Every piece of tool, from the invention of the wheel, the hammer, to the car to the computer is defined as technology.

So what do I mean when I say that web analyst will soon be replaced?

As a web analysts you are dependent on various tools to do your job successfully. Web analytics tools are constantly evolving. They become more complex capturing more and more of a company’s business. Many tools allow you through the API send in offline data and combine it with the online information they show.

Looking at today´s tendencies we see that the integration of Business Intelligence and web analytics tools are becoming more prominent. A fellow analyst told me not long ago that web analytics is just a technology to collect the data that then is put into his BI tool. From that he controls all aspects of his business.

As tools develop so does the capacity to start predicting outcomes. Predictive analytics is strongly growing and more and more companies use it to create a data driven culture.

Predictive analytics is in essence the marrying of data with statistical methods. When you do these interesting things start to happen. You can start understanding if you daily changes in metrics are for real or just normal.

For example Google Analytics uses this method to show you some of your metrics are significantly off the norm. Taking this a bit further the more data you put into a tool the more it will be able to understand the correlation between your data hence being able to predict what will happen if a value goes up and down. From this step it is not far to create a tool where you get recommendations what to do to boost your bottom line, today the job of a web analyst! You see where I am getting at? When the tools have been smart enough to start predicting and suggesting outcomes the next step is for management to start asking why they should have a web analytics department at all. This is the time when they will fire you.

Now, you might think this is a bit far-fetched conclusion but let me though put this into perspective through an example.

I read this interesting book about technology that leads to automation. Automation leads to loss of jobs in many different fields. It is also strong driving force for outsourcing. Without todays IT tools and Internet technology much of the outsourcing would be impossible. The most popular medical profession in the US is to become a radiologist. As a radiologist you work office hours and get paid a lot. Your job is to interpret scans of an x-ray machine. A big hospital today needs several people of this profession but more and more hospitals are outsourcing this to India. They send their scans through a secure Internet connection to India where doctors interpret them for a tenth of the salary a doctor in the US would do. Without the Internet technology this would of course not been possible.

Now you ask yourself, how does that relate to you as a web analyst? Well, it is already today possible to outsource part of a web analyst job to another country, but the biggest threat is not outsourcing it is software technology.

The next big leap in IT technology will not be hardware base but rather software base. Today’s software is rather primitive. The technology is moving so rapidly that if you start programing a software solution today and it will take you two years to complete when you are done it will probably already be out-dated.

Predicting the future is not an easy thing but almost all scientists within the IT technology field agree that within this century we will create artificial intelligence. That means computers that learn from their environment and their experience. Imagine what implications this will have for all areas of society and nonetheless for software development. A few years back ago I was discussing this option with a programmer. I told him to imagine a computer that can write millions of lines of code in a day and constantly review how the code works adjust it and deploy it all without the interference of humans. No need for a big team of developers that need to coordinate themselves. No need for human mistakes. Just clean beautiful code that works perfectly.

When the AI day comes, we will all be in trouble since it will touch all areas of society. But for now if you are a web analyst you should worry more about how your tools will develop within the next decade or so. To avoid being misplaced you need to figure out how to move up in the food chain. Understand how to create true value to your business which can probably be done in many different ways but keep an eye on jobs that need human creativity and idea generation. These are probably the last jobs to be replaced by a computer.

As a web analyst since you work with data you are probably in the best position to move into new fields. These new fields will probably combine the understanding of the power of data with the combination of creativity. So don’t be discouraged just keep an eye for change and you will probably do fine.

What makes a good web analyst?

A great web analyst can move the revenue needle.

I have seen a couple of posts about this subject (post 1, post 2) but most of them focus on the traits or actions a web analyst should have and take. They are mostly written from an outside in perspective. My aim with this post is to write the inside perspective, with that I mean how I as a web analyst think in my daily work. After reading this post you should be able to get into my shoes and view the world as I do.

It has been about four months since I changed company. I absolutely love my job and my new company. Since the online department is more or less brand new, we have several challenges in front of us.

If you have followed me you will know that I think a web analyst is in the absolute core of a company, at the very heart, since you can guide people to make great decisions. Being in this great position you need to make most of it. Therefore I think a lot of how I can help my company to excel to the next level. Putting my web analytics and conversion hat, glasses and gloves on you should think like this:

  • I should be on top of all web numbers. It is important for me to understand my site and the cycles that drive the business. I spend a bit of time looking a different numbers and contemplating about them from different angles. I should also control all measurement and expand it accordingly.
  • I should know the behavior of our users on the site. I think this is one of the most important points to be able to take your knowledge to the next level. I refuse to do reporting. Reporting is for dashboards and automatic reports; I should only do insights and recommendations. That is when my full potential is being used.
  • I should know what most of our users get triggered on when making a purchase. This user insight is worth its weight in gold and can only be found if you combine many different factors.
  • I should support key players in our organization to make better decisions. This might be through emails, reports with analysis, discussions, workshops etc. I think that as an individual I cannot succeed if my fellow colleagues cannot succeed.
  • I should guide marketing efforts towards the most valuable solutions. I deep dive into marketing actions to try to understand each component of that action. For example if it is email, I need to understand what the optimal form factor is, the optimal expressions etc. Each channel has its own mysteries that I should understand.
  • I should advise in all web page design creations, to get the conversion perspective in there. Every web page you create should have an aim and it should work with the rest of the site. Therefore you need to understand the various aims of each section of your site.
  • I should challenge key persons within the organization to push for new boundaries. With knowledge found in numbers one of my most important tasks is to push to explore new boundaries.
  • I should challenge partners we work with to be on top of their game. Measuring correctly gives me the power to know exactly how our partners perform.
  • I should own the conversion field. I know how we could use the web to drive more business. I use many different tools but the most powerful is AB testing. With that I can elevate the online business towards new highs.

These are the key points in my view of web analytics and conversion. My current aim is that our department should be one of the sharpest online departments in Sweden so view the list from that perspective. Every company has its own challenges and as web analyst you have to adapt to your environment. Although I think most of the points above are universal, but what will make you a good web analyst is if you in the end can move the revenue needle no matter which method you use.

Web analyst part of the revolution

I have been working with data in various ways for about ten years by now. I have worked both with collecting data, processing surveys, managing workshops, analyzing strategic data and now lately as a web analyst and conversion specialist. Being in the business for a while I have seen the transformation towards a more data driven society. For example the last two years the web analytics field has literary exploded. New tools and features are being introduced weekly. Companies are craving to handle their data and more and more companies are in the process of hiring web analytics people. The data revolution is hitting every sector of the economy.

In an outstanding article in the Economist about the data revolution one could read:

“Revolutions in science have often been preceded by revolutions in measurement,” says Sinan Aral, a business professor at New York University. Just as the microscope transformed biology by exposing germs, and the electron microscope changed physics, all these data are turning the social sciences upside down, he explains.

The Internet has contributed to this explosion of data as the article continues with Wal-Marts huge data sets:

Wal-Mart, a retail giant, handles more than 1m customer transactions every hour, feeding databases estimated at more than 2.5 pet bytes—the equivalent of 167 times the books in America’s Library of Congress (see article for an explanation of how data are quantified). Facebook, a social-networking website, is home to 40 billion photos. And decoding the human genome involves analyzing 3 billion base pairs—which took ten years the first time it was done, in 2003, but can now be achieved in one week.

Of course no human is able to handle these huge data sets therefore a lot of resources are being put on tools.  The amount of digital information increases tenfold every five years and the industry grows with over 10% yearly, roughly twice the software industry. The tools are getting more and more sophisticated and analytical methods are being built into the tools. For example Microsoft’s search engine Bing are examining 225 billion flight and price records to advice customers whether to buy an airline ticket now or wait for the price to come down (Farecast).

The article in Economist supports my general feeling I have had lately that the role of data interpreter, call it web analyst, BI, statistician or something else is heading towards a crossway. In the companies that are in the forefront of the data integration the need for a traditional web analyst is morphing towards a more converting type of analyst or even towards a strategic business developer.

From my perspective I see two major trends:

Trend A – More and more companies realize that data is a critical part of their business and the world spins faster and faster. This puts a lot strain on their data collection and their data use in making the correct business decisions. In this case the role of the web analyst is usually more of technical sort, handling the tools, understanding their requirements and supporting the organization on KPI´s and creating ad hoc reports.

Trend B – The data tools are getting smarter by the year. For example the field of web analytics is merging more and more with traditional BI. As the tools get smarter they are doing more and more the work of a traditional web analyst. KPI reports are handled automatically, ad hoc reports can be subtracted instantly without any special knowledge, correlation reports and basic insight is generated by the tool. In this case the role of the web analyst is either more like a statistician who handles all data input or a more evangelist like where one interpret or support business decisions.

For a web analyst both of these trends are favorable since the occupation becomes more popular but they demand two different types of skillets. In both cases the value of data lies in how we interpret our data. A combination of good tools and smart people will always be needed but the role of generalist is becoming more and scarcer, since more people will need to have special skills in various areas.

How many companies have web analytics or conversion departments today? I see this changing in the future. The BI and web analytics function will merge and the department will become a key player within the company.

As a web analyst in the future you have to consider what type of trait you bring to the table when the tools will do most of today’s traditional web analyst job. Focusing on the business value is a must but in what way? I keep pondering on how this development will go and I have no clear answer at the moment. Maybe you do?

“The data-centered economy is just nascent,” admits Mr. Mundie of Microsoft. “You can see the outlines of it, but the technical, infrastructural and even business-model implications are not well understood right now.” – Economist, Feb 25th 2010.

Yes, numbers lie

Have you ever read an article about a conversion increase? It is not uncommon to hear three figured increases, which sounds absolutely fantastic. With a three figured conversion increase it must mean that a lot of people are getting very rich, but of course the truth usually is a bit more complex.

I have stressed in my posts about the importance of having statistical significance in your tests before you draw conclusion but guess what, that is not always enough. You will also need to look at the number of conversions you get to understand your conversion increase.

First lets me briefly explain the significance concept. This is what Wikipedia says:

In statistics, a result is called statistically significant if it is unlikely to have occurred by chance alone, according to a pre-determined threshold probability, the significance level. The phrase “test of significance” was coined by Ronald Fisher: “Critical tests of this kind may be called tests of significance, and when such tests are available we may discover whether a second sample is or is not significantly different from the first.”

In plain English a statistical significance shows you how accurate your results are. So, if say you have a 95% statistical significance it should be read as, if you do this test a 100 times, 95 of these you will get the announced result.

Now, let me with an example show how statistical significance is important but not enough.

So, we wanted to try a new AB testing tool. We installed the code on the site, I read the manuals and I went ahead with a so called comma test. Actually it was a dot test. A dot test is when you put a dot somewhere on the site and then let it run as an AB test. In this way you should get the same conversion rate on both versions.

Below you can see the results of the test. Notice the fairly high amount of visitors on each version. I had several goal metrics. The Continue button, RefiForm2, RefiForm3, RefiForm4 and the thank you page. As you can see the Variation 1, which is the B version with the dot, had a 29,1% conversion on the continue button while the Original had 25,9%. Also the thank you page had 1,0% versus 0.6% for the original.

Both metrics point towards that this test increases conversion but of course you know better. Notice the confidence level. You need to reach five dots to be significant. None of these two metrics are significant, although the continue button shows a fairly healthy significance of 76%.

Now notice the RefiForm3. It shows significance with 99%. Does this means we should open an champagne and publish the results on a conference? Of course not. Even if the results show us a significant result if we look a bit deeper we can see that the winning version has only 22 conversions which is an extremely low number to draw conclusions from. As a rule of a thumb I usually look for 150 conversions or preferable around 300 conversions.

Further I have to consider what we are testing. Obviously there is no logic that a dot should increase conversion. Then I also look at how the test has performed during time. The graph above is a bit short but if you let it run for a while you should get a good illustration on how good the test has performed.

When interpreting testing results you have to consider several factors. Significance is a very important metric but not the only one. You have to combine it with the number of conversions and some time with a graph over how the test has done over time.

I hope that next time you come over a successful AB test that shows an incredible increase in conversion you should question the metrics. On your own tests, please do not try to be trigger happy, even if your stake holders push you for fast results. These things should be able to take time or there is a big risk of drawing the wrong conclusions.

To conclude you should:

  • Always look for significance in your testing.
  • Look at the number of conversions, are they to low?
  • Consider conversion over time, how it has changed.
  • Understand if the test makes sense.
  • And finally always consider the conversion interval.

If you have any questions do not hesitate to ask.