The Ultimate Guide to Leveraging Web Analytics
One of the speakers at last week's Internet Marketing Vancouver with interesting insight was Michal Lorenc of Google. He describes the internet as having 3 stages:
• Read, before 1998 where Google and Yahoo were introduced;
• Buy, between 1998 and 2003 where the eBays and Amazons of the world reigned supreme;
• and Talk, post-2003 where we have Skype, Facebook and Twitter.
The second day of the event held a great amount of value in describing web analytics to leverage higher conversion rates, and this guide is inspired by that.
I want to start by defining analysis. Analysis can be defined as the breakdown of a complex topic into smaller parts to gain a greater understanding of the topic. Stéphane Hamel of Cardinal Path referenced the Wikipedia definition in describing analysis but made a small change. His definition of analysis is how a business arrives at an optimal AND realistic decision based on existing data.
Hamel specified 3 ingredients to any analytics: People, Process, and Technology. I’ll be roughly using this framework to recap the thoughts of IMC Vancouver. The following is a collage of what one can take away from the many speeches during the event. (Part 1 of 3.)
PART I — PEOPLE
Before I dive into the framework, I want to explain the basics or Hamel’s online analytics maturity model. The maturity model is meant to analyze all functions of web analytics both online and offline and further close the gap between current and desired states. Hamel explained his model as having 6 areas in which to focus on in doing digital marketing analytics.
In these 6 areas there are 5 maturity levels for which a company to strive for:
0 – Impaired
1 – Initiated
2 – Operational
3 – Integrated
4 – Competitor
5 – Addicted
With a maturity level of 5, an organization will make drastic changes based on the analytics. Web analysis isn’t just a tool but a strategy embedded within the company. With a maturity level of 0, it means that this ability is nonexistent. The idea of the model is to analyze one’s organization and to spot areas that need improvement in order to provide balance across the 6 areas. I’ll say this line throughout this article: what is both realistic and optimal for one’s organization? Remember that not all companies have the capacity to get to the fifth level of maturity but it is important to first analyze where one is, and then try to achieve the next level ensuring not to focus on just one area of all 6 in harmony.
The first of the 6 areas fall into the people section: Management, Governance, and adoption (MG&A).
MG&A’s 5 maturity levels can be derived from asking the question “What is the highest job title fully accountable for online performance management against business objectives?”
0) No one
1) Project Manager
2) Team lead or Director
3) CMO
4) Senior Chief Officer (has high support of CEO)
5) Everyone in the organization is engaged in the process.
What is both realistic and optimal for one’s organization? The first step is to see where one currently lies amongst these 5 maturity levels. A smaller company will usually have an easier time to reach higher levels of the maturity level in this area as it is easier to make dramatic transformational changes.
Great people will have the ability to adapt with an organization and truly transform to a synergized team. Get your unfair share of talent and build your organization around these people. Andrew Bailey and John Gagne of Proximity advocated not only finding adequate people, but finding exceptional people. As they put it, good is the enemy of great. Sometimes the tough calls have to be made and it is okay to get people mad sometimes. There must be a belief that the one has the right people in your organization, and that the wrong people are off.
Great talent with diverse backgrounds is the cornerstone of innovations. As Hamel stated, once you stop innovating, you start failing.
PART II — PROCESS
Objectives are the second area in Hamel’s maturity model. He makes the time tested SMART objectives as the way to approach making well aligned goals. The maturity levels for Objectives can be measured by asking “what is the objective of your current online analytics program?”
0) Not defined
1) A Task list exists: Things one wishes to do
2) eMarketing optimization: Focus on optimizing the online channels
3) eBusiness optimization: Focus on optimizing all of the online channels and processes
4) Business optimization: Online and offline processes are optimized
5) Reinvent Business: Business strategy might be reviewed by analytics
What is both realistic and optimal for one’s organization?
How to get objectives was covered by a few people in the event. The most useful piece of advice I found came from Jim Stern’s “The Human Side of Marketing Analytics” presentation. He described some companies have a tendency to first create a message and then find the right people to give it to. However, doing the exact opposite would be much more efficient. Listening to your customers is a great way to create your goals. This idea was reinforced by many presenters as being a much more efficient way of creating a message.
There is so much available data today that it is hard to decipher what to make of it. As Sterne said, goals should be tied down to bottom line. With web analytics, the wealth of data sometimes blurs this idea and the wrong things start to be measured. Lowering costs, increasing revenues, raising customer satisfaction should be what we try to measure. Not how many people clicked through, but how many people did the desired action.
Ross Jenkins and Michael Hayward reinforced this idea in stating that it is important to measure what matters, which does not mean to measure everything. Marketing campaigns work together to achieve outcomes.
Scope is the third area of Hamel’s Maturity Model. This can be derived by defining the size of the fields on wishes to play in, specifically which platforms one wishes to engage in. The maturity levels can be described as follows:
0) Improvising: going with the flow not fully completing profiles or any real strategy.
1) The HIPPO: means the boss calls the shots into which platforms will be used.
2) Specific activity or sector: Scope is limited to one platform or one activity (ex. Tweeting on twitter)
3) Single Website/Channel: All aspects of a single channel like a website.
4) Ecosystem: possibly multiple websites, mobile, online/offline activities, and Social Media.
5) Beyond online: Online and offline activities are looked at even business functions.
What is both realistic and optimal for one’s organization?
Stern conveyed the importance of understanding one’s limits. How much people one can reach is an important variable to factor. There are so many people in the world; there is no hope in trying to reach everyone.
Jenkins and Hayward described explained that organizations build around channels, customers do not. Since customers are on multiple channels, organizations should adapt and provide customers with different avenues of interaction. Before, businesses would have most of the control in how the messages were given; now the landscape has changed and the power is with the consumer. However, how exactly can this be done?
Jenkins and Hayward described 2 ways in how to focus which channels to use: Attribution models, and campaign stacking. For example, say a customer got an email, clicked an ad, and used a search engine before they bought a product online. What do you credit for the sale?
A 1st click attribution model means that the email would get the credit for the sale as it was the original point of contact. This model favors awareness marketing, is good for doing keyword research, but the downfall is, how far back do you go? Will an advertisement a customer saw 2 years ago really impact the sale now?
Last click attribution would mean that the search engine gets the credit as it is the last point of contact. This model favours search engine because consumers will usually use a search engine to find the place to buy the product. It emphasizes keyword searches over the long tail strategy. It is best suited for short goal cycles.
Weighted attribution models attribute it the sale on a curve. It will put weight on all the channels but it is a judgement call. Tools do not do this on the fly and some extra manual work must be applied. I find this method to make the most sense yet as it seems to always go, it is the most difficult to employ.
Finally, campaign stacking is a very useful way of attributing sales to the used channels. Google multichannel funnel is a prime example of this. It basically shows which channels we’re used and at which times. By using this technique, one can see what really drove the sale and what was important in the sale. See here for a better overview of how campaign stacking works.
Structure is the fourth area of Hamel’s maturity model. Simply answering how one has structured analytics for online. The maturity levels can be described as follows:
0) No dedicated resources.
1) Project Team: Members of a project are responsible for it as part of their work description.
2) Full time analyst.
3) Distributed team: There are many people focused on it with different backgrounds.
4) Multidisciplinary team: A distributed team is working solely for Web analytics.
5) Empowered business users: Information is easily accessible and all business users are able to obtain their required information. The multidisciplinary team is used as a support function.
Continuous improvement proves and analysis methodology is the fifth area of Hamel’s maturity model. This area can be analyzed by looking at which methods are used to analyze information. The maturity levels can be described as follows:
0) None.
1) Own way:, otherwise put, it simply exists.
2) Own Methodology: A company is using their own methodology that is being employed.
3) Proven Methodology.
4) Agile Methodology: Hamel describes programs like “lean 6 sigma” as a good example for this. It allows for multivariate testing.
5) Agile organizations: The whole organization can adapt to change quickly and efficiently based on data.
PART III — Technology
Leveraging the tools, technology, and data integration is the sixth and last area of Hamel’s maturity model. Note the word ‘leveraging’ as it isn’t just using these resources but being able to use them right. The maturity levels can be described as follows:
0) To be decided: there is no data or lack of tools
1) Clickstream/behavioural analytics: Simple surface level analytics with no customization
2)Defined outcomes, Key Performance Indicators/Dashboards are being measured.
3)Segmentation, merchandising optimization, A/B testing etc.: Data is being integrated with business goals
4)Multiplicity merging data: All data is being merged and utilized as one. All processes and toold are looked at for optimization
5) Predicative analysis: This is the proverbial crystal ball. Being able to use all the data and predict customer behaviour effectively realigning organizational strategy
What is both realistic and optimal for one’s organization?
This is by far the most interesting of all the areas. It is also where the model all comes together. Hamel’s 6 areas are based on fixing the process, business, and people behind analytics to tap into the complete potential of leveraging the tools and technology for what we need them for.
Shaping data to make it useful is very difficult to do. The pinnacle of web analytics is finding the right data to tell us what customers are trending towards.
Here are some of the tricks learned at IMC Vancouver on how to better use the tools available to us.
Advertising space on webpages used to be very small and rather restrictive. However, the introduction of banner advertisements has changed that. Statistically, a banner advertisement outperforms regular advertisements in all measures and provides great improvement across the marketing funnel (awareness, consideration, conversion).
Chris Goward of WiderFunnel had great insight in using the analytic tools to increase the conversion rates on WebPages. The first step was to create powerful hypothesis and then to test these hypotheses. A powerful hypothesis is testable, seeks to solver conversion problems, aims at improving marketing results, and builds on marketing insights.
He used the lift framework to structure his powerful hypothesis. The lift framework is based on increasing the value proposition a website or and channel provides to the customer. In order to increase the value proposition, one must focus on increasing:
1. Relevance
2. Clarity
While decreasing:
1. Anxiety
2. Distraction
3. Urgency
If the focus is to increase people signing up for a website and there is a landing page to signup, don’t distract the reader with widgets, news feeds, or other unnecessary things. Simplify the interface.
By adding a security icon beside a payment, sometimes it increases anxiety as it brings up security in the minds of consumers which may not have even been there before.
Once a hypothesis is established, design a second interface and test the response against the original interface. This is the premise of A/B testing which is widely used to optimize conversion rates. Also, by tracking the conversion rates on both the original and new designs, one can truly start to understand what customers respond to.
Goward used the example of a hair loss website. One interface had mostly facts and statistics of success; the second had pictures of models. In this case, the facts won over the models.
A/B testing can be used to put any two designs against each other regardless of which platform it is. Email, Webpages, and banner advertisements can all be improved by this method.
Another tip from David Jenkins of Build Direct is the use of email. He states that email that is triggered after a response has a ten times higher conversion rate than simple blast emails. If you want your email to be more effective, make it automatically sent once an action is taken. He explains that 90% of leads on the web go cold in an hour which is why this trigger email system is so much more efficient.
PART IV — INSIGHTS
Hamel started his presentation by saying an organizations success can no longer be measured by how much money they have. These days, other important factors are to be used:
• Customer Satisfaction
• Icon in industry
• Ethics
• Corporate citizenship
• Employees
The Royal Canadian Mint presented a case study of how they used web analytics to increase their revenues and customer satisfaction. They knew their website was lacking and it was providing customers a bad experience. However, they could not find a way to measure customer satisfaction.
Without numbers to back there hypotheses they couldn’t ask for more funding to revamp the site. However, they soon made a survey asking questions about usability, performance, enjoyment and other metrics. After collecting results they had something to go to upper management with.
Once they employed this survey they were able to reach level one in Hamel’s maturity model in leveraging tools, technology and data integration. They measured customer satisfaction was 59 out of 100. It was a start and they have since completely expanded their web presence.
They used A/B testing to see measure how much more revenue was generated with the frequency of emails going out. They didn’t want to hit a wall where customers would start ignoring them but they didn’t want to lose out on potential opportunity.
After realizing the positive effects email had on their revenues, they started focusing on email acquisition. They created focus groups, and asked users what they would like to see improved. Essentially, they were learning more and more how to use web analytics and integrating it into the organization.
Today, The Royal Canadian Mint Website accounts for 35% of revenues and unique users are up by 49%. Furthermore, the customer satisfaction rating they measured increased from 59 to 78 out of 100. They are continuing to find ways to improve their online presence and they realize that the future is going to be mobile.
The future of Web analytics is going to be based on collecting and merging data. As it stand it is difficult to track the information of different people because there is no easy way of saying the person who used their phone is the same as the person that used a computer. Today it is based on cookies, but a more effective way is to have customer profiles for them to sign in.
Soon enough, the most successful firms will be able to customize their message to their audience individually, across many platforms, targeting how it best engages them. Online videos already outperform TV ads on every metric.
Clearly, the power of web analytics will be absolutely vital to engaging consumers in a way never thought possible.
