Web Analytics 5Cs
I bet you have heard about Marketing Mix 4Ps (Product, Price, Place & Promotion) or Entrepreneurship Funding 3 Fs (Family, Fools & Friends).
I thought it was about time Web Analytics got a marketing-like-named framework (so far we had Trinity). Here is something lighter you can use to explain your job, pitch a prospect and also as an initial analysis strategy.
Web Analytics’ 5Cs are, Campaigns, Content, Customers, Conversion and Competition.
Campaigns (/Traffic Sources)
- Which traffic sources are driving the most traffic to your site?
- Which traffic sources are driving quality traffic to your site?
- Which traffic sources are efficient (cost-revenue wise, ROI analysis)?
- What does a traffic source can tell me about that visit
Content (/Product Offer)
- Which contents are more popular?
- Which contents/products generate more revenue?
- Which contents are entry points to your site?
- Which of those contents have high bounce rates?
- Which content are driving organic traffic (through what keywords)?
- Which contents have high exit rates (any of those is part of a funnel, form or conversion process)?
- What features are working (insite search, tag clouds, dynamic content blocks)?
Customers (/Visitors)
- What is your rate of returning visitors?
- What % of your visits sees more than n page views per visit?
- What % of your visits stays more than t seconds per visit?
- How does the recency histogram fluctuate over time?
- What is the geographic origin of your visits?
- Can you segment them based on metadata available at login or based on behavior on your website (survey, forms and keywords)?
Conversion
- What traffic sources have higher conversion rates?
- Which contents have a higher impact on conversion (Google Analytics Money Index)?
- How does a conversion funnel perform?
- Are there any products with a better conversion rate? Is this general or specific for traffic sources, visitor segments or content paths?
- Can you identify visit segments with high conversion rates (low hanging fruit)?
Competition
- What is your competition doing (SEO, Adwords, Ads, offline)?
- What is your competition offering?
- What share of traffic is your competition getting (Hitwise, Compete, Google Trends)?
- Is your competition HOT (Buzz monitoring)?
This post is just a reference and I’m probably missing several ideas that could be added to this framework. If you have any they are welcome.
I’m happy you put “Competition” on your list; it still is a very neglected aspect of Web Analytics. If competition is only at “a click away” as they say, how can one measure that competitive pressure?
It is a very important fact of online business life too that your competition influences your numbers, but we still overlook that aspect when it comes to measurement.
Jacques Warren
16 Dec 08 at 5:46 pm
Hi Jacques,
I really think in the next 2 years will see more products offering this kind of market/competition monitoring. Currently since is not that easy to integrate competition data with your Web Analytics tool most analysts choose to focus on what can be done with the data on hand. It’s a very healthy approach but I’m sure as data becomes available and we are able to integrate it with our traffic and customers knowledge new business opportunities will be spotted.
Andrés
17 Dec 08 at 5:10 pm
Good ideas, but what kind of tactics can a person put against these kind of answers below? They are good to know, but if your in ecommerce, people not staying long are probably not a customer, those who do stay long may be doing their due diligence or having difficulty and the others are buying. I suppose if these %’s were to swing wildly it would indicate something going on, but if they are a certain consistent %, how do you influence them?
What % of your visits sees more than n page views per visit?
What % of your visits stays more than t seconds per visit?
Brian
18 Dec 08 at 5:28 am
Hi Brian,
I agree with you that depending on several factors not all questions are relevant and/or as important. Said so, with respect to your comment…
Not all sites have the same business model. If you are a content site which main income comes from advertisement knowing which % of your visits stays longer than t seconds or visits more than n page views could be as important as the average time or page views.
For an ecommerce site these 2 particular questions could not be as relevant, important or actionable as others.
But if you are interested in knowing if the Information Architecture or Usability of your site works, comparing the add-to-cart rate for visits with more than t seconds with those that spend less than that time on your site could be a good starting point.
When analyzing how deep to place certain contents knowing than 60% of your visits don’t see more than 3 page views can be relevant.
I wrote a post last month on segmenting your audience using criteria like the ones you mention on your comment (I use Amused, Addicted and Aware visits).
http://www.webanalytics.cl/11/2008/aware-amused-addicted-aaa-analysis-a-spin-off-to-eric-peterson%E2%80%99s-engagement-metric/
I segment visits to try to characterize my audience and hopefully link these segments to revenue generation. Establishing revenue per visit and/or conversion rates for each segment and monitoring these metrics in time help me spot problems or validate changes. But then more questions arise (it’s an analyst life
).
Are there segments of the site’s visits that perform better (revenue wise) than others?
Can we increase the amount of visits from these segments? (Driving new traffic? Turning visits from other segments?)
Cheers,
Andres
Andrés
18 Dec 08 at 10:06 am
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