Web Analytics in practice: your online analytics strategy – how to get started?

[This post is the third post of the Web analytics in practice series - practical posts on various topics based on my own daily experience – as a practitioner. It aims at providing tips, advices and examples that – I hope – may inspire and help you – whether you are a beginner or more experienced Web analyst]

In my view, the role of a Web analytics expert goes beyond than just implementing tags, reporting and analysing data. It is also his/her responsibility to develop the online analytics culture. In order to succeed in this perilous quest, he/she needs to have a strategy!

Ok it’s easier said than done. Everybody would agree that “all we need is a strategy” but practically, how do I define such strategy? Well, I don’t have the pretention to teach in a post how to create your strategy but at least, I would like to share with you some hints on how you can get started. Ready? So, let’s start first with the key aspects you should consider.

The critical factors for success
In Web analytics, the focus is too often on the technology, the tools and the data. “What?! There is something else?” you might think.  Of course there is! If you want to make Web analytics a successful practices (you know delivering insights, driving actions, adding business value and all), you must address the following factors:

• Management & governance: Who does really care about Web analytics? Who’s managing it?  Just the analyst? A project manager? Top management level? Does anyone know where it is going? Governance is essential as it will unlock access to budget and resources, it will make changes in the organization (i.e. breaking silos) possible.

• Objectives: what’s the main goal of Web analytics? Optimizing specific tasks or the overall customer experience? Optimizing online marketing? Or does it serve to improve business efficiency including offline processes – within marketing and other departments? Too often organizations expect a lot from Web analytics but have no clue to what they really want to do with it.

• Scope: What are the boundaries of your web analytics “playground”? Are you looking at limited, specific areas of your site (e.g. check out process, campaigns...)? The whole site? All your “e-cosystem” (e.g. social media, intranet, mobile...)? Other factors will depend on the complexity of your scope.

• Resources: Who’s working on web analytics? Do you have dedicated resources? Are they working part-time or full-time? Do they have the required skills (business, technical and analytics)? You can have ambitious goals but you need to have the manpower and skills to make it happen. What’s the point of spending lot of money in a super- tool if there is no one to exploit it?

• Process & methodology:  How do you translate business needs into KPI’s and measurements? Everyone having his method or is there a department/company methodology? How do you ensure that insights drive actions? Do you have any process for checking data quality? Too often efforts are put in implementing measurements and delivering reports but then we move to the next projects – providing little insights and rarely driving actions.

Then comes the factors we love so much to talk about:

• Tools & data: What tools do you have and what tools do you need? What are you doing with them? Basic reporting or advanced KPI dashboards? Are you equipped to cover different areas of web analytics (multiplicity rules!)? Are you integrating online data with other sources (CRM, BI data, market research, competitive data...)?

If you know Stéphane Hamel’s Online analytics Maturity Model (OAMM), these factors will sound very familiar to you. Indeed, I took these from Stéphane’s model as I think it is very complete, relevant and most of all very practical.

Getting started: current situation vs. Ideal situation

Now that you know what you should consider in your strategy, you need to assess where you are and where you need to go.

You need to evaluate your current situation using objective and well defined criteria for each area. Instead of reinventing the wheel, I really advise using Stéphane’s OAMM methodology (I do use it). You can do this by yourself – make sure to be really honest and objective as much as possible. Another possibility is of course to call for external help (but then it requires budget that is not always easy to justify). And because Stéphane is a really nice guy, he even has developed a FREE assessment online tool. Go and give it a try!

Evaluating your current situation will require you to gather all necessary information regarding the above points. Do not under estimate the work. Go around your organization, meet marketing managers but also other department managers (IT, sales, product research...). The extra benefit from this is that you will meet important people and it will get you some visibility. Never a bad thing!

Once you know where you are (a good starting point), the next step is then to set your destination where your company needs to get, based on the knowledge you have gathered.  It will be your ultimate target, your ideal situation. Note that not all organizations need to reach highest level for every factor. As usual, it all depends - a good understanding of your business and organization will be crucial. Make sure to review your work with your management.

One element I like a lot with the OAMM is that it is a very good communication tool. You can easily visualise both situations – current and ideal – using a radar chart (see examples below). Why doing this? To show gaps between where you are and where you want to be. It will help you highlight your biggest weaknesses.

From there you can define a high-level roadmap with main goal being to get to a balanced situation i.e. reach a similar level for each criteria. Split your roadmap in phases where the goal should be to move one factor to the next level - one step at a time (Kaizen approach). Do not try to jump several levels in one go – it will not work.

Practical examples
Let’s illustrate the principle with two different examples (note:  these examples are fictitious examples of course – any resemblance with real cases would be pure coincidence. Or maybe not ;-))

Example A:

Company A has very ambitious objectives (optimize all e-business) and scope (everything online, from web to social media). It has an analytics champion working full time on analytics who has defined some methodology and process within his department but not especially applied within all the organization. The company uses dashboards and KPI’s but mostly relies on one single WA tools –integration with external data is almost inexistent. Basic segmentation, no testing. The big problem is the lack of governance. Apart from project manager level – no one at senior management level is really taking ownership and having Web analytics in his/her top priorities. The current situation is depicted in the left diagram below.

The second diagram (on the right) shows where company A should ideally be (=long-term target) to leverage the added-value of web analytics (i.e. moving beyond reporting).

What’s next (mid-term target)? The company needs first to get strong governance otherwise no way it can get the support to get extra resources to cope with the ambitious objectives and make process known within all departments. It also needs to do more than web reporting and must consider A/B testing, segmentation and valuable analysis techniques as well as integrating data from outside the web (CRM, sales...). Again without strong management support, it will be difficult to upgrade technology, break silos and change mindsets.

Example B:
The situation is quite different for company B, management is taking the lead and ownership – there is a strong support from higher level (director level) and the objectives are currently limited to e-marketing optimization. Focus is on the main websites. Because of strong management support, company B just hired a dedicated full-time analyst. However there is no process in place and while there is a tool implemented, it has been used so far for standard reporting.

The aim of management is to extend analytics to other business areas and go beyond just online processes and integrated online data with other sources (CRM, offline channels...).

What’s next? Here priority should be on establishing appropriate methodology and process in order to define adequate measurements & KPI’s – first at department level before extending it to other areas. This will help leverage the use of available technology before adding other tools and integrating online data with customer & offline channel data. Achieving data integration will allow expanding objectives outside the online scope only to other business area.

Moving further – some more tips
This is just the beginning but at least you should have identified key areas to develop.  There is of course a lot of work to do from there - you will have to break down each target into practical projects or initiatives before getting management approval. But it’s a start. To conclude this post, here are some more practical tips:

• Set achievable targets:  think about SMART objectives and take into consideration politics, organisation capacity, internal culture, available budget... Having a strong knowledge of your company and business is essential.

• Set the right priorities: address first most important levers such as management and resources. You will see that technology & data will often come after (except if you really suck in this area)

• Convince your direct management first i.e. the person right above your (i.e. your direct boss). Once you have got his/her support – it will be easier to get to the level above. 

• Track your progress and review your strategy on a regular basis – every quarter or 6 months for example and align your plans based on your progress and changes of your business environment

• Think big - start small: be ambitious but remain with your feet on the ground. Start with small practical pilots to demonstrate your case – it will help you move forward.

• Prove your claims: to get support and convince management, you will have to back-up your plans with tangible evidences (i.e. ROI, added economic value...). If you can not answer why it worth investing money and time, you are doomed.

Defining your strategy takes a lot of time, effort and experience but it is a must have if you want increase your company maturity – past the initial level. Trust me.

I hope you have found this post interesting and practical. Such a difficult subject I must confess. May it inspire and help you moving Web analytics maturity further in your organization. Good luck

What do you think? Do you use the OAMM? Or any other model? How do you practically define your strategy and roadmap? Any experience you are will to share with us? If so, please do.

Related posts:

• Web Analytics in practice: Campaign tracking & offline advertising (Sept 2011)
• Web Analytics in practice: Using segmentation to drive insights and actions! (Oct 2011)
• Web Analytics – plan, do, check and... ACT! (July 2011)
• A journey into Web Analytics (Part III): Critical factors for success  (Aug 2010)
• A journey into Web analytics (Part IV): Web analytics, a new profession? (Sept 2010)
• Defining actionable & business-driven KPI’s – a practical methodology (Nov 2008)

Related resources:

• The Online Analytics Maturity Model white paper by Stephane Hamel
• The Online Analytics Maturity Model Assessment tool
• "Rethink Web Analytics: Introducing Web Analytics 2.0" by Avinash Kaushik

Web Analytics in practice: Using segmentation to drive insights and actions!

[This post is the second post of the Web analytics in practice series - practical posts on various topics based on my own daily experience – as a practitioner. It aims at providing tips, advices and examples that – I hope – may inspire and help you – whether you are a beginner or more experienced Web analyst]

If you really want to do true analytics then segmentation is essential. I like to think that if you are just looking at aggregated data, you are only doing reporting. If you want to do analysis, segmentation is the way to do as it leads to valuable insights that, in turn, will drive business actions.

While there are several “common” ways in segmenting online data – true segmentation requires putting in the effort to have a good understanding of your business (what does matter, key goals...) and to find your own meaningful segments. Such exercise will help you sharpen your business expertise - always a good thing.

In this post, I propose a step-by-step simple example (based on my own experience) to illustrate how to apply “standard” and context-related segments, to drive insights and the resulting actions.

The case: analysing the performance of a key landing page
(Disclaimer: for confidentiality purpose, actual figures and results have been modified but I have kept the general order of magnitude and the resulting learnings are true ones)

The context
The mission is to analyse the performances of a landing page that is the entry point for new customer acquisition. The page depicts the product offering and key benefits. The main goal (or outcome if you prefer) of the page is to drive traffic to the acquisition process. (Note: for this illustrative example and to keep it simple, I will limit the scope to this simple “micro” goal).

The metrics used: traffic volume to the page, number of conversions (outcomes) and of course the conversion rate.

Start:  no segmentation – aggregated level
A quick query in the Web analytics tools returns raw numbers that look like this:

These are just...er, numbers. What do they tell? Nada, nothing, niets, rien! The number may be nice for some or ridiculous for others. Who knows? (Even me, I couldn’t tell if these were good or bad as it was the first time I got my hand on this area).

1st level segmentation – by traffic source type
If you are a regular reader of Avinash Kaushik’s blog (or you have read his book – “Web Analytics 2.0"), you may have heard about what he calls the “best Web analytics report” (page 85 in the book :-)). A good way to start is by segmenting by traffic source. It is quite an “universal” way to segment.

 I start first with key traffic source types: “direct” (in this case coming from site), search (all) and paid channels (banners, affiliates, emailing but not SEA). This already gives a different picture:

At this stage, there should be some alarms ringing in your head. Look at the paid channels! It performs 8 times less than the other ones while it brought almost 90% of the traffic but account for less than 50% of conversions. Ok, we know that typically such channels so not perform so well but still! Like the detective we are, we got a first clue so let’s further investigate!

2nd level segmentation – by paid channel
Focusing on the paid channels, we can segment it one level deeper – by paid channel and I trend the result over time to add more context to the analysis. (Again, in order to keep the example simple, I have limited it to 3 paid channels). Now we are seeing something very interesting:

 Affiliates traffic suddenly went through the roof – causing at the same time a massive drop of the conversion rate. Almost time to talk to the digital campaign manager but before let's gather some more insights and let's segment a level deeper: by actual sources.

3rd level segmentation – by referring source
I look specifically at the affiliate channel and split it by referring site to end with a report very similar to the Avinash’s “best report in the world”:

The results clearly highlight big discrepancies between referring sites – those related to saving & financial topics are performing rather well while the rest is doing very poorly in spite of bring huge amount of traffic (typical of affiliates).

Now I have enough and I can go to talk with the digital campaign manager (and not just sending an email with figures) in order to share the insights. If cost is related to traffic then urgent action is needed (= wasted money). If not related to volume but per conversion then the question is: is it really useful? What is the lead quality? Is it positive for the brand (for visibility and awareness)?

At this point it is up to the manager to decide. My role is not to tell her how she should do her job - I would not dare to - but to provide her with insights so she can take data-informed decisions.

Using contextual segment – customers vs. Prospect
Similar segmentation can be applied to search channel – organic vs. paid then at keyword level but I guess you get the picture. Now let’s apply a different segmentation – what I call contextual segmentation i.e. that relates to your own business context.

Working in the bank industry, there are two main types of visitors to the website: customers  and prospects. I can easily identify the former group using a visitor-based segment: visitors who have logged in the online banking area in current or former visits.

Why such segment? Because there is no way customers can be "converted" so by aggregating these visitors in my results, I don’t get a true representation of the actual performance of the content and process for the intended audience i.e. prospects.

The analysis shows that customers represent a significant share of visitors coming from search – these land on the page and they use the site navigation to log in or to browse the content. Now calculating the conversion rate for the prospects gives a much different results as illustrated below:

See the difference between the “average” performance and this segment? Amazing, isn't it? The insight here is that prospects coming via search are highly qualified. What can I do? Get more of these segment to the site. How? By reviewing SEO aspects of the page (meta tags, copytext...) and optimize it (and there was work to be done in that area :-)) and considering putting some more money on SEA.

The analysis also demonstrates that the page is maybe not doing so bad after all. Just looking at aggregates could have lead to a typical (bad) reaction: “let’s redesign the page – it sucks!”.

Segmentation -  a powerful analysis tool
Segmentation can be applied on many criteria: sources, behaviour and others. Be inventive! Segmentation is a way to translate a business question into an analysis that will help bring the answer. Typically, segmentation will lead to new questions that in turn, will be translated in more detailed segmentation.

I hope that I have illustrated how segmentation moves you from reporting to analysis. I must confess that I fell in love of segmentation. Once you start, you can’t stop. This stresses the importance of having tools that give you such ability, tools that make it possible to do in a flexible and dynamic way. Segmentation on the fly is not an option. It’s a must! 

Taking segmentation to the next level
This post was a just an illustrative example and there is much more behind segmentation.  If you have the possibility of linking your online data with CRM or customer data then you can do even more advanced segmentation: by customer segment, by product, by demographic, by persona... It will pave the way to more valuable insights and customer intelligence. Segmentation climax will not be far away! More on that in a future post...

So, was the example a good illustration of segmentation? What are your favourite segmentation criteria? What “own” segments are you using? Do not hesitate to share your feedback and own experience on that topic. I am very curious to know.

Related resources & posts:

• “Web Analytics in practice (#1): Campaign tracking & offline advertising” (Sept 2011)
• "Web Analytics in practice (#3): your online analytics strategy – how to get started?" (Nov 2011)
• “Web Analytics Segmentation: Do Or Die, There Is No Try!” by Avinash Kaushik (May 2010)

Web Analytics in practice: Campaign tracking & offline advertising

[This post is the first post of a new series about Web analytics in practice. The idea is to write very practical posts on various topics based on my own daily experience – as a practitioner. It aims at providing simple tips, advices and examples that – I hope – may inspire and help you – whether you are a beginner or more experienced Web analyst]

We all know how to track online campaigns (banner, SEA, affiliates, social media...) – it has become quite a common practice (if not, you should better get started now!). It is really basic stuff.

However campaign tracking should not be limited to the online world. What about the offline activities that may drive traffic to the online channels? In this post I would like to cover two common offline sources that typically (should) bring traffic to your online properties: friendly  URL’s and Quick Response (QR) codes commonly used in offline ads.

Print ad's & short URL’s
It is very common to use short or dedicated URL’s in print ads (magazine, billboard, brochures...) that are (supposed to be) easy to type such as www.toyota.de/yaris or www.deutschebank.be/effecten (the latest was used in print ads in newspapers and displays). These short URL’s redirect you to specific online content (that often has a much “longer” not-so-friendly URLs).

But how effective are these URL’s?  Are they worth the space they use on the advertising space? Are people really typing these?  Everyone can start arguing – giving his own opinion but the only way to answer the question is of course to MEASURE IT.

It just works the same way as tagging any campaign URL – instead of using the plain URL as destination, configure your redirection using an appended URL with campaign parameters.

For example:
Let’s say I want to use a short URL such as www.mysite.com/newABC that goes to a new product page www.mysite.com/products/news/productABC.html. Using Google Analytics (but it works just the same way with any other Web analytics tool), I would use the following URL as destination of my short URL:

http://www.mysite.com/products/news/productABC.html?utm_source=offline&utm_medium=display&utm_campaign=ProductABC_launch

The advantage of using such common method instead of relying on server stats (that are not always that easy to get) is quite obvious:

• Availability & centralization: Everything is in one place with all your other online data.Iit gets in your Web analytics tool directly – not need to ask an external provider or IT to get redirect figures.
• Consistency: it gets measured on same platform and same way as any other traffic sources - you are sure to compare apples with apples.
• Segmentation: You can leverage the power of segmentation and isolate online behaviour, conversions for visitors coming via this source (and benchmark vs. other segments).

Quite simple and straightforward, isn’t it?

Quick Response codes

In this age of mobile – quick response codes (aka QR codes) are getting everywhere and replacing short URL’s in ads. After all it is much easier to scan a QR code(well, in theory :-)) than typing an URL no matter how short or friendly it is – as long as you have mobile device that can scan such code of course.

In most cases, the QR code is simply added somewhere on the ad or in the brochure for example. Sometimes, some brands are using these in a more creative ways. For example, Victoria Secret in the US leveraged its product “sex-appeal” (or should I the persons wearing the product :-)) and made an intelligent use of QR codes to “encourage” people (well, mostly men actually) to scan them.

Anyway – back to topic - whatever way you are using QR codes in your print material, in the end the important question is: are they driving traffic? Do people really take the time to scan the damned pixel thing or are they just skipping it?

Again the only way to find out is to measure. And it just works the same as short links. The URL that you use to generate the QR code should be a properly tagged URL.

Example:
If I want to generate a QR code that will redirect to my blog post on PDCA approach, I will use the following link:

http://www.kaizen-analytics.com/2011/07/web-analytics-plan-do-check-andact.html?utm_source=offline&utm_medium=QR_code&utm_campaign=PDCA_post

The problem with tagged URL’s is that these can get pretty long and this has a drawback when used to generate QR code: it gets quite dense and may be therefore hard to scan. But there is way to solve this issue: once you have defined your tagged URL, use an URL shortener (such as bitly.com) to get a much shorter URL and then use this one in your QR code generator. You will get a much cleaner QR code – easier to scan  (kudos to Luna Metrics for providing such clever and simple tip!).

Again using such common method for QR codes presents the same advantages as cited previously: centralisation, consistency and segmentation.

Do the right people know about it?
To be honest, tracking such offsite sources is not rocket science and it is quite common sense for whoever has been doing Web analytics. I am certainly not the first one to write about it. But still – it is not something that is systematically done. Why? Because the main hurdle is not at all technical – it is somewhere else.

Most of the time the problem is more a lack of awareness and communication. In many organizations, offline marketing is often managed by different persons than the ones who manage online marketing. Most of the time offline marketing is not aware about the tracking possibilities (and how simple it is) while the Internet marketing is not always involved in the creation of offline content (until the moment they see it – but then it’s too late). So how can it be tracked if the right people don’t know about it?

So it is your role, as a super Web analytics evangelist to inform your marketing organization. Seek out the offline marketing team, explain them what can be done and – most important – the added-value it will bring. But don’t stop there – on the first times, guide them through the process (generate the links or QR codes), show them the results and bring insights until it becomes part of their normal content creation process.

It is not a matter of technology here – but more of process and communications. It’s all about teamwork!

To conclude regarding the use of friendly URL’s or QR code, based on my own experience, I would say that the results were not really impressive (to say the less) – at least as online traffic driver. Maybe you will get better results but then it is up to you to test different approaches, creatives, etc. Especially that as you can measure it – you have no excuse for not testing!

Now it’s your turn now: what is your experience with such offline techniques? What other offline techniques or channels are you also tracking online?

About the post, did you like this first post of the series? Was it useful? Practical or not at all? Please share you feedback. I will definitely take it into account for the next posts.

Related resources & posts:

• "Web Analytics in practice: your online analytics strategy – how to get started?" (Nov 2011)
• "Web Analytics in practice: Using segmentation to drive insights and actions!" (Oct 2011)
• "Victoria’s Secret Entices You To Scan Their QR Codes" by 708media (Aug 2011)
• "Tracking QR Codes in Google Analytics — Easy as Pie" by Luna Metrics (Aug 2011)
• "Tracking offline world using online tools" by Capstrat blog (Sept 2010)
• "Measuring the impact of offline events with Google Insights for Search" (Feb 2010)
• Example of online QR code generator