Web Analytics - Challenge or Opportunity?

A recent eMarketer study published a chart showing the areas of knowledge that web analytics users worldwide would like to improve. Here are the top few:

1) 60.8% - measuring web 2.0 technologies
2) 57.2% - Targeting & Segmenting
3) 49.8% - A/B and Multi-Variate Testing
4) 48.6% - SEO
5) 41.2% - SEM

Other areas included, campaign & content management, email & affiliate marketing, each recording <38% response.

I find this interesting because, while a lot of organizations struggle to keep up with the right and effective measurement, users like us, with an elevated passion for web analytics, can grab this as an opportunity to create competitive advantage for our respective business units.

For measuring web 2.0 technologies, DEFINE your goals for promoting your business on blogs and social media sites, SET key performance metrics and MONITOR these KPIs for best results. Data in this area is in its nascent stages, and metrics such as, reach, velocity, engagement, followers, loyalty, etc. are still gaining popularity. The challenge in not only in measurement, but also in applying the insights, if there are some to be gleaned from the data.

Targeting and segmenting ideally needs to be on 2 fronts - consumer-centric and content-centric. Ideally there is significant overlap, or else, we need to first build greater insights into our consumers and business objectives, before attempting to target our content.

A/B testing is fairly common, but in my experience, businesses often struggle with multi-variate testing, due to a variety of reasons like, lack of tools, resources, expertise, etc. Investing in this area can help solve for multiple metrics, resulting in significant improvements budget utilization and user experience.

Marketing campaigns (SEM & SEO) analysis is relevant for obvious reasons - optimize your search term buy for best return, and invest in SEO expertise to apply techniques for improved rankings.

The closing thought is that we should not try to be good at all of the above at the same time, since the business teams tend to lose focus with too many initiatives and may not be ready to measure/analyze/recommend most efficiently. Evaluating gaps in your business will help develop a strategic roadmap to prioritize and implement these initiatives for best results.

What is a good conversion monitoring frequency!

A few days back, I did a quick poll on how often we monitor our conversion frequency. Needless to say it ranges from daily, to once a week and once a month. There is no benchmark for this, but the intent was to increase awareness about the conversion itself. Being aware of the conversion from our site is critical, if we want to achieve the desired outcome.

If our goal is to drive the traffic deeper into our experience, we need to make sure that users are in fact clicking on the the links to other relevant content on the site. If our goal is to drive revenue, we need to ensure that users find the right product or listing on the landing page. Page design and site layout should account for these user needs.

Tools such as, Click Map from Omniture allow one to look at click frequency across all links on the page, and can help determine the success on such parameters as, position, design, color and other User Interface features. These should be inherent to any design process, that caters to evolving user needs and changing market conditions. Monitoring frequency will then be based on how rapidly we can collect and analyse the data, and make necessary changes to our site experience.

Take for example: Amazon is consistently driving the user down the conversion funnel, and consistency of experience is key for returning users, hence monitoring frequency once a week may suffice. However, CNN may need to monitor user tendencies on a daily basis (even hourly), to determine which stories are keeping users engaged, so as not to bury them in the site as new stories break. In either case conversion monitoring should be conducted as frequently as needed to maintain a healthy consumer engagement and an eye on your business goals.

Guide to making Web Analytics more accurate!

A recent eMarketer study identified top issues with the accuracy of analytics. Most prominently, users said they can't drill into the data (42%), and called out the issues with marketing attribution (32%), campaign tracking code (25%) and cross site analysis (20%). These factors become prominent as the business evolves over time and market driven changes are incorporated across the site. However, with some planning and framework, we can define and implement a robust analytics strategy that is flexible and adapts to the evolving business needs and site-wide changes.

The first step is to take a step back and outline the core strengths of the business, around which metrics will be defined. This means that if we are a content focused site, we need to ensure the page view depth, SEO traffic growth, etc., are top measurement priorities. Further, monetization strategy of this traffic should be defined, in close coordination with sales and business development. (The exercise needs to be repeated at the page and/or section level). For an ecommerce site, it will be highly desirable that conversion metrics are aligned with the strategy, traffic engagement and monetization.

Web sites have three key ingredients that define its performance.
1 - traffic into the site
2 - navigation behavior within the site
3 - conversion from the site (usually lead/revenue generating click)

The key to a robust site analytics data is to be able to connect the above 3 ingredients in a flow that helps explain the value of the user coming into the site. In my previous experience, we ran into several issues in trying to develop reporting that provided this level of visibility.

Basically, a campaign code assigned to a particular promotion needs to be tracked through the navigation cycle, up to the point where user leaves the site. This helps us understand which campaign drives most traffic, how do users from various campaigns interact with our experience, which campaign drives maximum value towards our internal goals (engagement, lead, revenue, etc.).

Ideally, it is best to work with ONE vendor in implementing the tracking and reporting system, so as to ensure consistency, data integrity and institutional knowledge - identifying a vendor that provides the best possible solution becomes much easier, once the step one above has been defined at the onset. Onsite staff that understands the business and the analytics implementation can then provide insights and recommendations that are sustainable.

Low hanging fruits in web analytics!

When I am looking for greater impact - macro trends in the data, I often come across interesting insights that can be easily implemented and rewards measured almost instantaneously. These observations, not only yield quick results, but also make a compelling case for continued focus on analytics (if it ever need to be emphasized!). I wanted to share an example to spur conversation and show how little nuggets can be utilized to create incremental value for the business!

While trying to understand the seasonality and return on our promotional campaigns, we started to see a pattern in the common terms within the titles that had resulted in a better click- through rate (CTR). Looking at the last 9 months's data and we founde the "theme" behind some of our most successful campaigns. One of the top 5 terms that emerged was "free" - not surprising in this economy, although I would argue that free will always be popular :) Free, while most obvious in retail, could mean a lot of things such as, free service, free trial period, free coupons, free gift, etc. We came up with campaigns that had free in the heading, and saw double-digit improvement in CTRs.

How to use "return frequency"

A few days back I spoke about the importance of return frequency (Are you looking at your return frequency, published on Monday, 11/9). I wanted to elaborate on how this metric can be applied to build a competitive advantage.

The purpose of a detailed analysis into return frequency is to "deaverage," i.e., help us understand our user segments and their corresponding site sections. We need to measure traffic at page level, aggregated to site sections, if that is relevant for your business. Secondly, we need to segment our users based on engagement with our content areas. The two data sets provide a unique look into site engagement that can be utilized to tailor the user experience.

Similar customization has been adopted in brick & mortar establishments for some time now, with a focus on streamlining product search and consumption. In a web experience, this can only be achieved when we track user data at page and/or site section level. Also, important to note here is that you should not be afraid to dump the pages/sections that are not meeting user needs and/or not aligned with your strategy and core strengths.

Once the data is available at this granularity, we can then understand if the user need is being met, monitor trending of popular pages in a given week/month and adopt editorial programming accordingly, and evolve monetization strategy based on targeted advertising, product displays, etc. This not only makes the site more dynamic and fresh, it also generates user interest that keeps driving return frequency. By the way, for you business planning folks, this data will be extremely helpful in defining strategic road-map and traffic/editorial/revenue targets for your next planning cycle.

Challenges with using web analytics in marketing!

In a recent study by eMarketer, top 3 challenges with using any web analytics data include; inability to integrate data with other marketing solutions (46%), verifying accuracy (41%), lack of comprehensive data (32%). Not surprising at all!

A couple of theories jump out of these findings. One, there is a lot of data that can be available through simple tracking with any of the wide array of tools in the market.

Two, not enough effort and foresight goes behind defining the success metrics and the data that needs to be collected.

Here, I want to address the second theory, since we can and should control it and demand more from it. The data needs for each marketing campaign fall into a tightly linked planning, launch and post-launch stages. If we are to take a guess, this is usually not the case!

It is imperative that the campaign strategy clearly defines success metrics, data needed to verify this success, and a clear implementation plan to ensure appropriate reporting will be available to analyse the performance. It should be made a part of the project planning process, with the campaign manager directly accountable for reporting on campaign success.

Professionally, I have been witness to several projects, where measurement and analysis could not be completed, because analytics department/individuals were not engaged from the start of the campaign process. Effective ROI measurement and future marketing investments are dependent on how robust our data quality is - that should be justification enough for engaging appropriate level of analytical and data support at the concept stage of each marketing campaign.

Are you looking at your "return frequency" data?

Return frequency is probably one metric that is representative of customer satisfaction irrespective of the industry.

In a web based business, however, it is both, difficult to accurately measure return frequency and hard to utilize the data (provided we have a good sample) to promote our business.

In most reporting tools, return frequency is reported at site level - that is, how many times an average user is coming back to our site. And, therein lies the problem. First, it is only speaking about an average user. Second, it is only measuring the metric for the entire site. Unfortunately, there is no such thing as an average user, and more than likely, your site has more than a few dimensions. Consequently, a site-wide metric is only good for an "average user" - not a winning strategy for any business.

So, the first step is to adapt your anlytics software to show page and/or site section level return frequency. Then "de-average" the users into defined buckets, and classify site sections based on repeat visitation data. Combining these two insights will help you understand why a user is coming to a particular site section/page at your site. You can then tailor the experience to meet "most" needs of "majority" of users to the above site section/page. The reason I say "most and majority," is to emphasize that trying to classify 100% of your site usage will probably not yield best ROI on the effort invested. Picking top 5 or 10 site sections, for above improvements, will be a good start.

Do you have a specific question on this metric or others that you would like addressed? I promise to move it up my list of topics to discuss :)

Why is my conversion low?

Ok, we have all struggled to answer that question. Conversion metrics are unique to your business, yet how we analyze these varies dramatically based on industry, web design, specific landing page, etc. Often, I find that websites try to offer too much to too many audiences. By that I mean, we tend to think that all of our users should be able to find what they came to our site for. The critical question to ask ourselves, "is my page designed to cater to my target audience, or am I being generous to all web browser?"

Take for example:



I like this page - has clear calls for action: "shop now" and "go" embedded with great values and find gifts respectively. No clutter, and clear enough for the consumer to quickly decide what they are there for.

However, I would argue that it is relatively easy to be direct, when you are serving a niche market segment, like in the example above.

Now, let's look at another shopping site serving a wider audience.



No clear call for action, no clear navigation to desired areas within the site and hope that audience are looking for holiday gifts in electronics.

We assume a lot about our audience needs, but not enough data to support these theories. The first step should be to define needs based on data. Next, define the goals and design the pages to serve these, with clear call(s) for action.

Liked this article? Want more on this topic? Have your own stories to share? Post your comments and I will be quick to respond.

Is the business Main Page enabling your consumers?

A lot is invested in creating that spell-binding first impression (our main page, or front door!), but are you doing all you can to ensure that the experience is in line with your consumers' expectations? I wanted to draw our attention to this often hyped, yet overlooked disconnect! Applying this concept to our web site may bring amazing results, not just in terms of conversion (this is unique based on our business goal/s), but also, consumer satisfaction, which drives loyalty and a positive "word of mouth" - all very important considerations!

The primary goal of your "front door" should be clearly defined, keeping in mind the needs of your consumers. Assuming, market research has helped you focus on the consumer need, the next step is to focus on your primary goals? Is it; branding, growing traffic, addressing a consumer need in your niche market, growing revenue, driving traffic to other parts of your site, etc. Once you chose the primary goal, the remainder on the list above can still be addressed as secondary goals, while staying focused on a positive consumer experience. One could also address more than one primary goal from the main page, but that starts to get into addressing a specific need within a niche market segment. A case in point - Google, which meets a critical consumer need for search and achieves several goals - high traffic, positive branding, etc.

So, the strategy should be identify/target a consumer need in the market segment, and tailor the experience to closely match your primary goal(s). Focus on one or the other and you risk losing consumer attention, loyalty and branding - all of which can hurt the business in the long term.