Increasing efficiency and reducing waste in digital analytics

Increasing efficiency and driving better digital performance is the essence of digital analytics. As analysts, that’s what we do: we look at digital data and try to understand where the threats and opportunities are for a business; we do this based on data, experience, judgement, common sense and business acumen. But here is the paradox: we, as an industry, suffer from a lack of efficiency and we produce a lot of waste. So I think that if our aim is to truly drive more efficiency for businesses then we have to look at ourselves and start reducing waste.
There are a few causes of this waste in my opinion. To me, the primary one is the obsession for digital analytics tools and I think we are all guilty of that one by the way. Then the other reason for this is a lack of processes for all the components of digital analytics. Last but not least, the lack of independence for the digital analytics function is also an issue.

1)The obsession for tools: come on vendors, you have to become more involved in the digital analytics journey!
I feel quite passionate about this particular topic which is why I had already written a blog post about this just over a year ago here ; if you have not got the time to go through this then as a summary I talk about some of the key people and process related questions your organisation needs to ask itself before purchasing an expensive digital analytics tool. When a business ends up buying an expensive digital analytics tool without really answering some of the questions I list in my previous article then not only does the business end up wasting money but most crucially there is significant waste driven by implementing a digital analytics solution which is not adapted to the business. There is also time wasted on training everybody up on it…Ultimately, this is time not spent on driving actionable insights.
Now, let’s say you have asked yourself/the organisation the right questions (around people and process) before acquiring a tool and you have decided that such purchase makes sense from a business perspective, great. But that’s when the troubles potentially can start and when more time is going to be wasted, and particularly the digital analysts’ time…
As a digital analyst, how much time have you spent troubleshooting your digital analytics tool? For example how much time have you spent trying to understand how the “Intelligent” marketing attribution filter really worked in Yahoo Web Analytics? How much time have you spent answering questions from the wider business on why, on Site Catalyst, the tracking code report would not match the marketing channel report? How much time have you spent figuring out why the direct traffic source in Tagman is over-inflated? By the way, if you are interested in the answers, then please ask me by posting a comment and I will answer but hopefully you get the idea: too much time trying to figure out discrepancies, oddities and lacks of consistency. Now, I do think these inconsistencies are not a problem in themselves as long as you know why but until you do, you will be spending and wasting a tremendous amount of time and energy finding the answers to all those questions.
I believe that part of the solution needs to come from the vendors themselves.
I do think they need to do more for clients, they have to be present throughout the whole digital analytics journey, not just at the beginning and on an ad hoc basis once the solution has been implemented to answer basic questions. I really think that a very good way for them to help us succeed consistently is to provide collaboration platforms where clients can share pains and eureka moments with each other and with the vendors themselves obviously. And guess what? Vendors would hugely benefit from this because that would free up some of their support staff. The other advantage of bringing in more collaboration is that this would enable vendors to create a co-creation environment between clients and themselves. Of course, we know there are digital analytics forums and knowledge bases dedicated to specific digital analytics tools and sometimes these have the answers to your questions but this is far too ad-hoc and inconsistent in my opinion.

2)The lack of processes in the digital analytics journey: a focus on the tagging “nightmare” we have all experienced.
I won’t go through the lack of processes throughout each of the digital analytics components here; instead, I will focus on tagging: the start of the data collection process, a key step, often neglected. Part of the reason for this can be down to high expectations coming from the wider business which wants to start seeing data ASAP after signing a big cheque to a digital analytics vendor. But that’s not the main point I want to make here. The point I am on about here is the lack of ownership around tagging. It does not mean that tagging does not get done, it means there is no process and no accountability for it; a tagging task is just another IT task amongst hundreds of other IT and digital development tasks. Even worse that that, it also means there is no tagging knowledge collected, documented or shared. And what’s wrong with this? A huge amount of waste once again as tagging tasks need to be re-done, re-taught multiple times.
It is not uncommon for the digital analyst to end up owning tagging for at least 50% of it. Personally, I have spent a huge amount of my digital analytics career looking after the tagging side of things: investigating digital analytics code, writing technical specs for developers, as well as testing their implementation. Not coming from a web development background I have learnt a lot during that process but I also had to go through huge pains and it meant that during that time I was not driving better digital performance, I was only making sure we were collecting data and the right data.
So, how do we make sure that tagging is finally 100% owned and managed in a business? This leads to my third point on why there is still too much waste in digital analytics: we have got to become more independent.

3)Digital analytics suffers from a lack of independence and needs to be a department in its own right.
Yes, this is high time for digital analytics to become its own department, not part of Marketing or IT or Operations (or even Finance…) Why is it so important? Because by operating independently from the other key business functions, digital analytics will become less ad hoc, more strategic and more visible. Let me explain…When digital analytics is part of Marketing, what type of analysis do you think the digital analysts will perform? Marketing analysis, that’s right. When digital analytics is part of Operations? Probably internal promotions type analysis or time series analysis after a new digital platform implementation (but not Marketing analysis). It does not mean that the digital analyses performed from within a department are not relevant and useful, they are but they are dictated by where you are in the organisation so they are bound to be focusing on one aspect of the organisation and one aspect only. And by the way, I think by being a function in its own right then a lot of the tagging challenges will disappear.
The other significant benefit that would be achieved would be the ability to create and manage your own digital analytics processes which would be the pillars of the digital analytics department. By processes here, I mean processes around the 6 pillars Stephane Hamel is describing in his great Econsultancy article .
As always, thank you for reading and I am always interested in hearing your views so do comment and let’s get chatting!

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Thoughts on the 2012 Adobe Digital Marketing Summit

For the third year running, I attended the EMEA Adobe Summit and I wanted to share my thoughts on what I felt was worth highlighting, please do let me know your thoughts too by commenting! I have broken this article down in 4 main parts. The first part describes the themes that stood out this year, the second part briefly highlights one of the new Discover 3 product features, the third part is about a web analytics heroes session and the last part is on one of the keynote sessions which was not about digital but which I thought was excellent…

How this year’s Summit themes reflected new consumer trends, the propensity to become more scientific and more precise:
I was comparing this year’s Summit agenda with the past two years’ (I do tend to keep things…) and it became obvious that there were 3 new topics that were taking a lot of space in this year’s Summit: Mobile, Predictive Analytics and Personalization.
-Mobile: don’t’ worry, obviously this was not around the fact that this year was going to be the year of mobile (I think we have all heard this every week for the past 5 years)…Mobile was one of the topics a lot of sessions were dedicated to, in fact it was one of the five main agenda themes. I personally did not attend the mobile sessions but I could not help but think about one of the key reasons why mobile was so big this year and I think it must have something to do with the launch of the digital wallet which is likely to shake things around very soon.
-The other theme that was very present throughout the whole day was predictive analytics. Again, this is certainly not a new sphere but it seems as if the industry is really trying to get a little bit more scientific when it comes to forecasting marketing spend and returns. The Efficient Frontier acquisition by Adobe is a very good sign of this shift.
-Personalization (not segmentation): this is also a theme that was largely talked about during the Summit. One of my favorite sessions was a debate on whether there was a conflict between personalization and privacy. I think what made this session very content “rich” was the diversity of the panel. It was lead by Martha Lane Cox who is one of the Last Minute co-founders and who is now, amongst other things, leading Go On UK. Martha started the debate on a very personal note by telling us about her very serious car accident and how the Internet helped her throughout her journey to recovery to stay connected with friends, family and life. The other people present on that debate were Andre Germinet from Credit Agricole (a French bank), his perspective was very interesting and unexpected, being a banker. To him, there could be a true social benefit in banks having access to more banking related consumer data and in banks being able to offer more personalized services. For example, if banks were more aware of individuals financial circumstances they could be in a better position to help and prevent some of these individuals’ financial situations from getting worse. David Dean from the Boston Consulting Group shared some really interesting statistics. The first number was the fact that when asked how much the Internet was worth to them, private individuals estimated this number to be around £5,000 a year; this number would be obviously a lot more for businesses. The other stat he shared with us was on the healthcare industry and on how it could save up to 30% by having greater access to healthcare related consumer data. Martha and Meme Jacobs who is the Adobe Chief privacy officer both felt that the future of the Internet was all about personalization. Everyone in the panel was in favor of personalization when Dave Evans from the ICO had a more cautious view and felt that more partnerships were needed between industries and consumers with the purpose of providing either more transparency or more value or both. So really interesting debate and to answer the initial question on the existence or not of a conflict between personalization and privacy, well, it’s all about context…

Discover 3 new product features
The other session I enjoyed was on Discover 3. To me, the feature which stood out was sequential reporting: you can now build funnels with multiple types of variables. For example, you can start your funnel with an evar followed by another evar followed by a product view event and then followed by an open cart even; as opposed to having to build your funnel on one type of variable only such as page names for example.

Web analytics kung-fu or web analytics as its best
I also really enjoyed this session as all the points tackled during this discussion were challenges that I have come across multiple times as a practitioner and it is always great to hear that some of the best in the industry do go through the same things!
Eric Crossfield from John Lewis insisted on the fact that ongoing communication on what the purpose of web analytics is is key as well as building trust with the people who will ultimately act on your findings. Adam Greco did a really good Site Catalyst exercise. He asked the crowd how many considered themselves not knowledgeable, good, very good and experts at Site Catalyst. He then asked the people who considered themselves to be experts to answer a very precise Site Catalyst question. No one was able to come up with the answer; I thought Adam’s demonstration was really powerful: knowing your web analytics tool is extremely important and you can never get too comfortable. I have personally always felt very strongly about the necessity of training people properly on web analytics platforms. Unfortunately this aspect is too often neglected in my opinion. As Adam pointed out, too often people will end up blaming the tool if they can’t find the answer to a specific question when in actual fact, the reason why they are not coming up with the answer is because they don’t know the tool sufficiently…
Brent Dykes, talked about the “from set up land to action land journey”. In my opinion this is a very long journey indeed. The technical implementation, the testing of the implementation and training a team can take months if resources are limited; consequently, action land seems like a long way away but luckily analytics as a function is slowly but surely making it to the top so I am confident that this set up land to action land process is going to become smoother as investments in analytics increase.

Last but not least Arianna Huffington from the Huffington Post gave a speech on what shall I say?… Life? Unfortunately, this is one of these brilliant sessions where you had to be there to appreciate it truly as my words won’t do her speech any justice. Arianna did not talk about digital or analytics or anything else we digital people do every day and My God that was refreshing! Don’t get me wrong, I absolutely love my job as a digital analytics consultant, I am passionate about marketing etc etc…But sometimes as individuals, it is hard to find the time to read or listen to something completely different because time is always limited. Arianna’s speech was genuine, intelligent, out of the ordinary and yet simple. Thank you Adobe for inviting speakers like this because this is truly inspirational.

Please, as usual let me know your thoughts, if you were there, let me know what you thought too and if not let me know what your views are on the topics described above.
Thanks for reading!
Penny

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Always overanalyse the business implications of getting a new web analytics tool

In the online world, new technology whether it is measuring technology or otherwise is constantly being thrown at us and this can be overwhelming at times.
One of the main reasons for this endless product/tool/feature release cycle is because the online industry is still growing and has not reached maturation yet. This is of course excellent news for those of us who work in this industry, as, another advantage on top of having a guaranteed career is that you continually get to try these new pieces of software.
However, because it’s really easy to get excited about all this, it’s also really easy to at best ending up being distracted if there is not the right thinking in place in the first place.

First of all, time invested in investigating a new technology is not negligible. You will want to understand what the features are like, research the competition, organize multiple meetings with the actual supplier, talk to the internal stakeholders etc…
If the technology is seen as a real problem solver, then it might even be purchased eventually. When that happens, an even greater amount of time will be required to implement the technology and then to exploit it fully. Now, I may be stating the obvious here but the latter part is often an afterthought. It may be because this is not the bit that technology suppliers will insist on, after all, their time is far better spent on boasting the amazing features of the tool or showing you reports containing data that you thought you could never get. It may also be because the excitement is just too great and it is hard to keep a cold head. To be fair to suppliers, anyone could argue that technically it is the client’s problem and responsibility to one decide who is going to be making sure that the tool’s potential is maximized and second to define the right process behind the tool. In my experience, this thinking and planning step is probably the most important part and yet the most neglected one.

What everyone must remember is that at the end of the day, a software is a software and that’s all it is; what ultimately matters most is the people that are going to exploit it and the process behind it all i.e the “How” bit, (that is assuming of course that the “Why the technology is coming into place” bit has been fully reviewed).
So here are a few things to consider during this thinking and planning step:
People:
-Who is going to be exploiting the tool?
-What measures are going to be taken so that these people’s workload remains manageable once the new technology is in place?
-Has the fact that these people’s time is much better spent on that new technology than on existing tasks been established?
-What level of training are these people going to receive?
-Who will benefit from the tool internally?
Process:
-Have the business questions that need answering from the tool been clearly defined?
-What is the internal communication strategy behind the tool coming into place?
-What is the road map for the tool?
-Are the people who will be acting on the data generated fully prepared to do so?
-Have the data delivery cycles been defined?
-Have the data delivery to data being acted upon cycles been defined?
-Is there a review cycle in place?
I think these questions are crucial to ensure success when it comes to getting a new web analytics solution in place. What are your thoughts? Have you gone through a proper thinking and planning phase before implementing a new technology or did you ever feel afterwards that the excitement had got the better of you?
Thank you for reading and please share your thoughts!

Penny

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Web analytics careers: web analytics is a whole world in its own right!

When I chose to go into pure web analytics 3 and a half years ago, I thought it was both a risk and an opportunity. My previous jobs had been in marketing where I got involved in all sorts of very exciting stuff from conducting market research to managing online, press and even TV advertising campaigns. I thought going into web analytics was risky because one, this type of job was practically unheard of at the time and second because it meant specializing in one area and one area only of online, marketing, e-commerce, IT; I could dedicate a whole post to where web analytics belongs or should belong but you get the idea that web analytics can belong to different departments depending on the company . The latter reason is also why this move felt like a real opportunity: specializing in one sphere means being an expert at what you do which I think is a very good and satisfactory position to be in.
Having said all that, what I have actually found out over these past 3 to 4 years is that although you do web analytics every day, you constantly evolve around very different areas: traffic acquisition, design&usability, web operations and web development. Because of this or thanks to this rather, your understanding of the web channel expands constantly and you can become very knowledgeable not just about web analytics but about other spheres despite doing web analytics everyday! That’s very good as it’s a way of discovering other areas of interest for yourself. Personally, I have discovered that I have a very strong interest in search and usability and it makes my job even more interesting. So web analytics can significantly expand your knowledge outside of pure web analysis.
Now, the reason for this post is that I have been thinking about the different avenues that a web analyst can take not outside of web analytics but areas of specialism within web analytics. To me, there are 3 routes: the technical one, the business one and the process one.
The technical route consists in translating business requirements into a web analytics vendor technical specification. There is obviously a heavy element of testing consisting in making sure that every single bit of code is populating a report (ideally the right one!) in the web analytics interface. I also know of web analytics technical consultants who spend a large part of their day fixing existing broken web analytics solutions.
The other route is obviously the business route and that consists in using web analytics to answer very specific business questions. These business questions can be as varied as: is there an opportunity for a mobile site? How much money am I losing every time my online payment system is failing? Which of my marketing channels are undervalued when I look at sales reports per marketing channel from a last click perspective? I think that’s one of the beauties of web analytics by the way: it allows you to spot business opportunities so it can reveal things that you would not have thought of otherwise and it also allows you to get closer to the truth by confirming things that you suspected already but was not able to prove until analytics came in.
The other route would be the process route. I really think that this is a route that has not been fully exploited yet by the web analytics industry. Processes exist to create more efficiency and to ensure that things are done the right way. Personally, I think that every aspect of web analytics should come with the right process in place. Data quality: has everything that is being collected been tested? Data reporting: is everything that is being reported on necessary? Is everything that can be automated really is? Data insight: is the data that is being sent being used? How? How often?
Personally, I have a preference for the last 2 routes because I think that implementing an analytics solution is only the start of the web analytics journey, not a goal in itself.
On the subject of the different web analytics routes that a web analyst can take , I should also refer you to Avinash’s post on the matter which I think is really good.
As always, I would love to hear your feedback on the topic. Do you have a specific route in mind? Can you think of any other?
Thanks for reading!
Penny

Posted in Web Analytics Careers, Web Analytics Challenges | 2 Comments

Practice web analytics when KPIs are up to understand why they go down.

Web analysts are a lot more likely to be tasked to perform web analyses when things go wrong than when things go well. If your site starts encountering a drop in sales or a significant rise in bounce rate, web analysts will be “strongly encouraged” to understand what is causing so much turmoil and the fearsome Why straightaway, no pressure here… One of the difficulties in carrying out web analyses in stressful situations is that your rationality level will not be 100%. The question is how do you adopt a rationale way of working in stressful situations?
If you want to be effective at finding out what is wrong with your site, you need to perform web analyses when things are going OK, well and fantastic. Why? Because it is a lot easier to come up with a list of items that you know contribute to your success and check against that list when things are going wrong rather than trying to think about all the things that could be the reasons why you are failing. Don’t get me wrong, the latter approach is very tempting, I know, I’ve done it!
If you have a list of your company’s, your website’s and your traffic’s pillars i.e your vital organs to check through, you will be a lot more likely to work rationally and productively and therefore come up with THE answers as opposed to answers. When things go wrong, your pillars list will actually become a suspects list to go through. That list of pillars will obviously depend on which industry you work in.
However, in my opinion, there are pillars that would be common to any website:
-Understand what your biggest traffic source is when things are going well and build strong relationships with the stakeholders for this traffic source. The reason I say strong relationships is because to me, knowing that this channel is your biggest traffic driver is simply not enough. You need to know not only what the current strategy is for this channel but also what makes it an asset for the business.
- Your biggest source of traffic might not necessarily be your highest converting source, (OK, in most cases it will) so also take a look at this one, get to know it inside out. As an example, you need to know the % of sales this channel represents when things are going well.
-Your conversion funnel, a conversion could by the way be anything from a purchase to an enquiry form submission. See what your continuation rates are between one step and an other throughout your conversion process when things are going well.
-Site Errors: make a note of the % of traffic that site errors represent when things are going well; sites errors might be 404s, timeouts etc…
-Your commercial facts : one of the numbers you might want to make a note of when things are going well is your average revenue per transaction.
-Your products: what is your average selling price for each of the product you sell when things are going right? What is the % of sales that each of the products you sell represents?
As you can see from the above, to come up with your list of pillars, an important part of the investigation work is dedicated to talking. That’s because, in my experience, it is crazy the amount of things that go on on a website and although as the web analyst you know what the numbers look like, you can very easily be among the last people to know about a product launch, a shift in the pricing strategy, etc…unless of course you talk to people and simply ask what is going on. But also, the information you get from people by chatting to them in an informal environment (so not by e-mailing them) can be incredibly juicy.
The pillars list does not end up here. As mentioned in two of my previous articles: Context is everything in web analytics not numbers and Context is still everything in web analytics some of your pillars will be external factors. In some cases, external factors will be more important than your internal ones. Yes, sometimes, all your internal usual suspects will actually be “released”, at least on bail… But it’s not until you turn to the external usual suspects list that things can become less blurry. Below are 3 examples of external factors that might be part of your pillars list:
-The weather: there are industries which are directly affected by national weather; travel is one of them. Repeated bad domestic weather tends to drive holiday sales up.
-Competition: look at your competition when things are going well for you and make a note of your conversion rate then. It may be that you are the only one selling a particular product; when everybody else catches up, look at your conversion rate again…
-Demand: what is at the origin of a strong demand? Well, maybe you have a monopoly on something but it could also simply be that consumers have money to spend. When things are going well, look at the statistics on disposable income, you can start by looking at the Office for National Statistics website.
So to summarize, you need to do web analytics when things are going well, come up with that list of pillars and have metrics against each of your pillars. When things are starting to look a little shaky, look at that list again and check the metrics again, chances are some/most of these would have changed and you can begin to explain what is causing disruptions and why. For example, if you notice that your average revenue per transaction is going down and that disposable income is also going down, then you can start by saying that economic factors are responsible for what is happening and not the number of errors people are getting when they are on your site.
So the idea of this article is to help you get to where you need to start and then to know what to check, that way, you can’t really go wrong.
The other thing that this article hopefully highlighted is that in order to be successful at web analytics, you need to understand that this is a continuous process, not something you only do when things become difficult. Web analytics is a journey, an endless one.
Let me know your thoughts!!!
Thank you for reading.
Penny

Posted in Web Analytics Challenges | 2 Comments

Omniture Summit 2011: My Highlights

I was lucky enough to attend the 2 day Omniture Summit EMEA this year in London and I thought I would write about it as it definitely was THE digital party of the year. The reason I loved that event so much was because Omniture have managed to make it constructive and entertaining at the same time. To put things into context, how many of you have been to a friend’s party which was constructive and how many of you have been to a work or career event which was truly fun?…
I think the 5 minute Youtube video is probably a good place to start.
Now, let’s cut to the chase and let me present you with my highlights of the Summit:

The constructive (and fun) highlights:
-Site Catalyst Improvements with Version 15:
1) Data normalization: this will allow us to visualize in a meaningful way sets of data belonging to very different scales. For example, let’s say that you want to graph your number of on site searches (assume you have 15,000 a day) and your number of sales (assume you have 50 a day). Without normalization, you would not be able to see your sales on the graph, let alone see any correlations between the two sets of data.
2) Real time segmentation: I have not used Omniture Discovery yet but I have had a demo of it and it was quite impressive what you could do with this tool from a segmentation perspective. Omniture were saying that some of the Discovery segmentation functionality would be present in version 15.
3) Integration with Test and Target: I think this is really cool to have your A/B testing tool integrated with your analytics tool. First of all because you can segment your tests based on previous on site events but also because you come one step closer to having all your analytics data in one place.
4) I should not be mentioning the fact that bounce rate is now a default metric, nor should I be talking about the unique visitor metric being available for any selected time range as these are not improvements in my opinion but rather problems that got addressed. Anyway, I thought I would mention them as I know they will make the life of many web analysts a lot easier…

-The web analytics framework byBrent Dykes:
I thought Brent’s framework was excellent as it showed all the parameters that are required for a company to be successful at web analytics. You need people, tools and process but you need to have a clear strategy around all this. Last but not least, you need to have the buy in from leadership. My thoughts on that would be that I would love to know how many companies have everything in place, particularly how many of them do have web analytics process in place. In my experience, process is the most challenging child of all…

-Optimize paid and organic search together:
I also quite liked this session, (partly because I like Search a lot). The session was all about how paid and organic search should be a lot more integrated with each other. Companies should have one search goal as opposed to one paid search goal and one organic search goal. I was struck by this because in essence this makes sense. After all, one could argue this is the search engines channel and there should be no separation. However, in my experience so far, I have always seen a clear border between these 2 channels: from the reporting side of things to the people who do the work.
The speakers then presented Search Centre +, this tool combines your paid and organic activities together; it is more than a traditional bid management tool in a sense that it allows you to shape your paid search bidding strategy around organic rankings: yours but also your competitors’.

-Provocative thoughts on web analytics by Matthew Todd:
I really liked Matthew’s session as it was so down to earth to the point where it became inspiring. He talked about the measurement problems that the web analytics industry should be addressing by encouraging a lot more transparency. As an example, we know that people use multiple devices to access the Internet everyday (I use 3 different ones on a daily basis) and this is bound to have a large impact on your uniques numbers.
Matthew then went into how web analytics can sometimes draw an incredibly harsh and simple version of the truth. For example, how many of us report on the success of a campaign by only looking at the number of sales and not pay attention to any other actions taken on the site, some of which could very much likely lead to a sale at a later stage?

-Social media by Brian Solis
I must state that his presentation was a true breadth of fresh air. At last someone talked about social media intelligently. Brian mentioned the existing gap between what companies think their customers want from social media and what customers actually really want from it. Brian then insisted on the fact that companies need to understand why they are doing social media otherwise they are bound to fail.

The fun (and constructive) highlights:
-Thursday night: the party with live dancing, painting, singing and great food all night.
-I really enjoyed Ann Lewnes talk, she is the SVP Corporate Marketing for Adobe. I liked it because first, it was good to see a woman on that big stage and also because she was saying that marketing was the new finance and as an online marketing person, it is very good to hear.
-Everyone got a copy of BOLD how to be brave in business and win by Shaun Smith right after Shaun’s talk.
-Brett Error’s talk, Brett is the VP and chief technologist for Omniture. Brett was the last speaker of the Summit and Friday afternoon was just the perfect time for him to come on stage, he really entertained all of us with his style, jokes and funny videos.
-I got to meet Adam Greco, Adam is a web analytics guru who currently works for Web Analytics Demystified. Adam and I had a chat about the different web analytics career paths that one can take; that conversation was very interesting.
-Finally, I ended my time at the Summit over a glass of wine with two web analytics consultants Peter O’Neill and Steve Carrod, both of them have their own consultancy, respectively L3 Analytics and Optibeat. We had a good chat on counter evars and tips on how to implement Site Catalyst.

So, to conclude, I can not wait for next year’s Summit!
PS: I have one thing to suggest to Omniture: why not have official networking slots? There were 1,300 attendants from all over the globe this year so what a fantastic opportunity to meet new people or to meet with your usual analytics geeks. The advantage of having official slots organized is that people can plan in advance who they would like to meet.

Thanks for reading

Penny

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Communicating efficiently on web data in writing: a daily challenge for web analysts.

Web analysts do a lot of thinking and a lot of research on their own on a daily basis. Yes, web analysts spend a lot of time with themselves. But the ultimate goal of their work is to do something with the results and unless analysts analyse their own site, they will need to communicate their findings to the “others” (yes, other human beings!).
I think it is all the more challenging when we, web analysts, need to communicate efficiently on something that no one asked us to do but that we feel is relevant. Why? Well, because our audience is not expecting to get some analysis, and our audience is generally very busy so how do we make our e-mails stand out from the crowd?
Actually, one might think: “Why should I have to make extra effort for my e-mails to get noticed? At the end of the day, it is a work e-mail and consequently should be read full stop!” Well, unfortunately, it is rarely the case. Our audience: colleagues and bosses are busy people just like us and will only tend to deal with the “urgency of the day” and too often will think: “yes, nice read but not for now”. So……….what tactics can web analysts adopt so that we are taken seriously?
I often think about my web analytics e-mails as e-mail campaigns. Therefore, I make sure:

1) I use a catchy subject line:
I always make sure one of the following words is in the subject line: Outcomes, Impact, Opportunities, Threats, Loss, Gain, Significant. Basically, I use words that make people want to open my e-mails, it’s as simple as that.

2) I send my e-mails at the right time of the day:
Yes, I try to avoid sending them at a time where people are either very busy (Monday morning) OR too relaxed (Friday afternoon).

3) I send my e-mails to the right people:
Now, that’s not always an easy one; although it might seem like it. The challenge consists in neither being too narrow nor too large. Let’s not be too narrow: for example, if I send an analysis on organic search, in some cases, I might want to also send it to the paid search manager. After all, both channels are linked with each other and therefore what is insightful and actionable for one search channel might also be relevant for the other search channel. Let’s not go too large: I try to only include the people that can actually take actions with the data. If I include too many people, it will be too impersonal and no one will end up taking any actions as they will think the “others” might do.

4) NEVER EVER send an excel document on its own:
Excel is dry, it does amazing things but I find the idea of opening an excel spreadsheet and look at data I am not familiar with very unexciting so chances are, other people do too. People should not have to open excel documents unless of course they want or need to dig deeper in the numbers. But the analysis provided should be enough. I still tend to attach the raw data (knowing that 50 per cent of the recipients will not open the excel document and rightly so!) in case someone asks for it.

5) Include words, numbers, context and graphs in my e-mails:
A good analysis is like a good recipe: made of a mixture of quality ingredients. At the end of the day, analyses need flavour and substance. Depending on what I want to demonstrate, I might want to use more words than graphs and vice versa.

6) Ask questions:
Sometimes, we might not have all the information needed to deliver a full diagnosis. So why not ask questions in our e-mails? I think it makes sense. Good analyses are the result of a multitude of pieces of data, and these pieces will not always come from the web analyst.

7) Follow people up:
Obviously, I follow up with face to face conversations/meetings to get feedback from my audience and to decide on what the next steps are.

I would love to have your feedback on this and please share any tips you may have.
Thanks for reading!
Penny

Posted in Web Analytics Challenges | 4 Comments

Context is STILL everything in Web Analytics…

Long time no speak, it’s good to be writing again!
Yes, context is still everything. By the way, in my previous post Context is everything in web analytics not numbers, I was talking about how Hitwise could give you market share information but not actual traffic numbers. They have actually recently upgraded their tool and you can now view actual numbers. But let’s now go back to our dear “Context”. In my last post about context in web analytics, I talked about the 2 main market elements that you need to be aware of as they are going to influence your site performance heavily: supply and demand. There are now other factors to take into consideration: internal and external factors.
Let’s start with internal factors. Internal factors are factors that you or your company has control over. I selected 3 factors below and gave examples of their potential impact on your site:
Internal Factors
So it’s about launching an internal investigation and talking to other departments in your company to uncover some truth. But an internal investigation is sometimes not enough, we now need to go external…
To do that, there is nothing better than a good PESTEL analysis:

P for Political: let’s say that you are a holiday company and Egypt is your biggest market, then your site (and your whole company) are both going to be significantly impacted by the recent political events that took place in Egypt.

E for Economic: during a recession, visitors are likely to spend less, which will have an effect on your site, (assuming you have an e-commerce site).

S for Social: with people spending increasing time on social network sites, companies felt that this could be an additional online channel worth exploring. Your site is now probably getting a lot more traffic and maybe more sales from social network sites than ever before.

T for Technology: mobile phones getting smarter and smarter means that consumers are prepared to spend significant time browsing the Internet using their mobile devices. That means traffic and sales to your site coming from mobile are likely to grow.

E for Environment: the weather is known to have a very strong impact on sales for some industries.

L for Legal: the new cookie law, starting in May this year will have an impact on everybody’s site: it is really hard to say how visitors are going to react to it yet but on site user experience is about to be “shaken”.

So, again, web analytics is challenging because there are so many factors to take into account before making sense of a particular number…Once you have identified all the factors that have an influence on your industry and market, the next step is a matter of knowing how much of an influence each factor is likely to have on your site performance. I think this is a very hot topic so I shall be writing about this at some stage but for now, let’s remember to always think about numbers with Context!

Thanks for reading.

Posted in Web Analytics Challenges | 1 Comment

Context is everything in web analytics, not numbers.

Web analytics is not all about numbers, in fact, numbers do not mean anything without context. Yes, numbers don’t mean it all. Let’s go back to basics and let’s take a look at the very well known business statement: your revenue does not mean anything, your profit does. Revenue does not mean anything because your revenue can be as high as you want it to be but it will never be an indication of how much money you are truly making. Having said that, your profit in itself and taken out of context is not as useless as your revenue but can be a useless number when taken out of context.
If your profit is £100K, is it an indication of how healthy your company is? Not at all. How does £100k compare to last month? To last year? Let’s say that it is actually up 2% YoY. Ok, things are starting to look positive. But hang on, the country’s GDP in which your company operates grew by 8% YoY and one of your competitor’s profit grew by 6% YoY. Does your £100K profit (up 2%YoY) look as healthy now? Not anymore I’m afraid…

I hope that this illustrated how important it is to look at numbers with a lot of context. As a web analyst, to get context, you can’t rely on just your web analytics solution. The good news is that there are tools that can give you just that. There are two tools I like using a lot: Google Insights for Search and Hitwise. Google Insights for Search is good as it gives you for FREE volumes indication of what the world has been searching for. It won’t give you actual volume numbers, Google actually normalizes the data and presents it on a scale from 0-100. Based on my experience, I have had discrepancy issues with the tool where I extracted data for a particular week on one day, came back the next day, extracted the exact same data for the exact same week and the results were different to an extent that meant I could not use the data anymore. So, I would bear that in mind and not take the numbers literally but look at trends instead. I mainly use the tool for Year on Year and Week on Week comparison to try and spot demand shifts.

The other tool I really really love is Hitwise. No, the two “really” in a row are not a mistake but a true statement of how I feel about this tool. Amongst so many other things it gives you an indication of your site traffic for a given market, or a “category” and for a set of competitors. Let me describe this a bit more: unlike a tool like Comscore for example,( great tool by the way!) Hitwise will not actually give you actual traffic numbers (at least it did not do this in 2009) but it will give you your site traffic market share as you can see on the graph I created below. For the purpose of this exercise, let’s say that you work in the automotive industry and that you are the web analyst for brand B. You are interested in knowing how your brand has been performing against brand A and C over the past few weeks.

Gain context with Hitwise

This graph is giving you a really good view of what has been happening in your market over the past few weeks. Something happened with brand A as its market share has increased over the weeks and it is now outperforming your brand! What have they been up to? Have they launched a massive TV campaign,? Have they gone viral on the web? Have they just launched a car which makes coffee and croissants in the morning? You guessed it, it could be anything but at least you now know that they are up to something and this could be one of the reasons why you have been getting slightly less traffic than usual over the past few weeks. Actually, one of the smart things about Hitwise is that when there is a sudden increase or decrease in market share, the tool will highlight for you in the graph major events that could have had something to do with it.

Using tools like this in conjunction with your web analytics solution can help build a better picture of the “WHY” as opposed to just the boring “WHAT”. Web analytics is complex in a sense that it requires merging different data sources together to try and make sense of what is occurring on your site on a given date. The tools described above are good at providing you with supply/competition and demand information which is a big step forward but there are so many other factors to be taken into account which can also have a major impact on you site performance. I will be talking about these in my next article so keep an eye on the blog!
Thanks for reading, I hope it was interesting and useful.

Posted in Secrets of Web Analytics | 1 Comment

How to provoke change with data

I wanted to follow up on my previous post Web Analytics and Change: Do these two concepts really go together? just so we don’t stay on a dark note and think that web analytics and change are two incompatible concepts. To me, for web analytics to be able to drive change, two things need to be happen. First of all, time needs to be allocated for this and second of all, processes have to be in place for this.
Let’s go back to the obstacles I raised in my last post. The first obstacle was the amount of people coming to you with very different questions about the site, the customers…To tackle that, I make sure I give new starters basic training on the analytics tool that is in use in the business. I also ask them about their job so I get an understanding of the type of data they can benefit from. That way, I can create custom reports for them straightaway, (and people love custom reports, it makes them feel a bit special!) Obviously, the same principles can be applied to existing members of the team. By doing this, you will save yourself and your team members some time. Time not spent on answering random questions on a regular basis means more time spent on higher value analyses that can lead to change.

The second obstacle I was describing was the amount of time required by the data collection process. In my opinion, there are two different approaches for this. The first approach is to review on a regular basis the amount of data that is really required; after all, businesses change constantly so reports should reflect that. The inconvenient of doing this is when you come to do an annual review and when you have altered your reports multiple times in the meantime, some of the data will be missing and it can be annoying. The second approach which is more practical than the first one consists in automating your reports. When I say automate, I mean automate, automate and automate again, so automate big time basically! Unfortunately and as described in my first post, not all web analytics tools have an excel plug in easy to use built into them. Now, depending on how many hours/days a week you spend on reporting, there could be a solid argument to justify switching to a more adequate analytics platform. Again, time not spent on reporting means time spent on analysing the data properly,and making recommendations that can drive change.

The last point I made in the previous post was the fact that it was very common for drastic changes to take place on a site without web analytics being taken into consideration at any stage. Now, this is a hard one to tackle because for this to change, it requires web analytics to be put at the centre of the decision process. This is hard to achieve because this means proper processes to be in place. Having proper processes in place requires the whole of your business to take web analytics seriously. It’s very easy to organise one meeting to talk about the data that will be required for project X. However, it’s an other thing to have these data driven meetings happening on a regular basis with key stakeholders. If not done already, I would really recommend you to read the web analytics business process white paper by Eric Peterson which gives some very solid grounds on this: The Web Analytics Business Process.
I would be very interested in hearing from anyone who has already implemented bits of what Eric is recommending in his white paper or any other web analytics processes of some sort.
Thank you for reading

Posted in Secrets of Web Analytics | 2 Comments