In a recent article on Ad Age, I came across an interesting article around increasing importance and emphasis on Dashboards. I always thought that Dashboards are native to analytics and that it ought to be adopted by everyone organizations by now. Aren’t discussion around Dashboard as old (even older) than Web/Multi channel analytics.

After reading the Ad Age article along with my experience with clients I have come across an increasing need by clients to PROVE the effectiveness and efficiency of ad spend. Presently, marketing executives appear to be singularly focussed on ROI. The question we ask ourselves is that is it the holy grail of all measures? Should we move away from ROI as a single measurement of performance and add other factors to provide a (more) comprehensive view or a meaningful picture of marketing effectiveness? If so how do we share or present this data? When we ask these questions the importance of Dashboards and Scorecards become increasingly relevant and important.

Are there any fundamental (building block) principles one can apply at a tactical level to drive this initiative…Here, we list some key principles we have found useful as practitioners. Call it the 3P framework 

Process & Priority

Whether you are a CPG, B2B, Telecom, or Retail it is critical to align yourself with your corporate strategy. If the priority is to democratize data then every effort should be made to integrate online and offline systems to share the data up and down the value chain. Usually creating a deployment plan for Dashboards is a good start. One doesn’t have to create an all encompassing, visually appealing dashboard from the get go. Start somewhere, even if it is excel, ensure data integrity, and most important think action/outcome as opposed to numbers. The next important area where organizations generally miss out on is creating target and benchmarks. If you don’t aim you can’t hit the target. Consider targets based on priority or goals based on historic measures and ad spend. This will be the first step towards transparency and data democracy in your business unit or organization.

Performance Measures

Ask yourself this question: If you were the top brass in your company or your marketing organization what would you care about? This question is easy at first but as you drill in you will find yourself in a rabbit hole. At least I still do. Executives will think about Branding, Voice of Customer, and Demand Generation. CXOs will always have an interest in understanding these activities. It’s important for you as a practitioner to obtain these inputs which ought to be the second step in the Dashboard creation process.

A CFO would care about:

• Net Present Value: How much value an investment will result in? Usually, this is done by measuring all the cash flows over time to a future date. If I had 100K in 1910 how much will the 100K be in 2010? Usually calculating NPV is difficult because you don’t know what discount rate to use (rate of inflation vs. Treasury index) but one can think in these terms when considering large scale projects and it’s potential return.
• Payback Period: Say you invested 100K in your marketing program, if it returns 50K per year then you would have a two year payback period. It is a good metric for calculating and minimizing operating costs.

A CMO would care about:

• Customer Satisfaction: It measures how products or services meet or better yet surpass customer expectations? In a competitive market space, CS is a key differentiator and a key element of business/marketing strategy.
• Brand Awareness: It measures the consumers knowledge of brand existence or recall as many like to call it. It is usually qualitative in nature.
• Cost Per: These are the compound metrics which Anil has written about and it’s all about integrating disparate data sources to provide a transparent view on the success of a program. I am sure you get the idea now, having carefully selected measures will not only allow you to get a pulse on the reality, it will also allow you assign accountability to the right people. If for example, customer sat is low, consider taking immediate action on areas where this can be mitigated. If your Cost Per’s are underperforming, you can pick up the phone and ask your marketing guy/gal/agency as to where or how the money is being spent and to have them consider optimization strategies.

Presentation

In the Process and Priority section I talked about this briefly. I have often seen that practitioners get too detailed. It becomes almost second nature for them to add more metrics. Usually, these are perceived to be intermediaries. It is really important to consider dashboard design. Keep in mind some best practices:

• Data overload: At most have no more than 7-10 performance measures. This way end users are not overwhelmed and data is actionable as opposed to regurgitable.
• Lack of Benchmarks: Smart marketers understand the value of benchmarking. Context is king. It allows you to measure yourself against past performances as well as set standards for ongoing campaigns.
• Scoring System: Consider the “traffic light” scoring system. This is a quick indicator and allows users to focus on areas which need attention. 

Thoughts? Comments?

This is a guest post from my friend and ex-coworker Kanishka Surana. Kanishka is currently the Head of Web Analytics for Ogilvy. He runs Ogilvy’s Web Analytics group in North America, he has been in the Web Analytics space since 2002 and has worked in London, Seattle, Greece, Seattle, San Francisco, Salt Lake City, and most recently in New York.
Before that Kanishka worked at Gerson Lehrman Group a pioneer in proprietary research space. Kanishka and his wife Mini live in New Jersey.

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
• Landing Page Optimization Analyst at Red Ventures Armed Forces – Europe

There are several misconceptions in web analytics (created by some author/bloggers/experts) though many others have tried to clarify them from time to time but they keep reappearing. I recently had a conversation with someone who was so much in love with one of the misunderstood metrics, listed below, that it prompted me to write this blog post. So without much delay, here are the most common five misconceptions that I come across all the time:

1. More Page Views are good – Unless you are an ad supported site that sell advertising via CPM (cost per thousand impressions) more page views might mean that the visitors are lost on your site and can’t find what they are looking for. More pages views/visit could indicate issue with your site navigation. For effective analysis, set your baseline and then watch for significant deviations (up or down) from the baseline.
2. All that bounces is bad – I have written 2 detailed posts showing why all that bounces is not really bad. Bounce rate is one metrics that people overly obsess with. Keep in mind all bounces are not bad. The things that cause high bounce rate are:
   1. Links to external sites that you want visitors to click
   2. Ads on your site take visitors out of your site
   3. Returning visits might bounce because they might come to your site to read your daily/ weekly/monthly update
   4. Visits that are for a specific reason e.g. find your phone number
3. Focus on reducing the bounce rate and everything will be ok- Well that’s the advice many people give without even looking at the other data points and analyzing if reducing the bounce rate will really help you achieve your goal or not. Reducing the bounce rate might not be the most effective way to increase ROI. You should create a monetization model and determine the impact that reducing the bounce rate will have before you start creating different version of a high bounce page to A/B test to reduce your bounce rate. I have seen cases where you won’t get positive ROI even when you reduce the bounce rate to 0%.
4. Time on site (or page) shows how much time people are spending on the site – As I wrote in my blog post titled Understanding the “Time Spent on the Site” Metrics there are many issues with measuring the actual time spent on the site or a page. One of the main reasons is that the last page that a user views/reads on your site is not counted in this calculation. So if you have a non-ecommerce sites then the chances are that the visitors spend most of their time reading the last page but that page won’t not counted in this metrics and hence your time on page and time on site metrics will be way off. As long as you know that you need to watch the trend instead of using this metrics as a absolute measure of time spent on site then go ahead and use this metrics.
5. Referring Sites report shows all the traffic sources including campaigns – Well… not really. There are a lot of reasons for the referring source to be lost from the time the visitor clicks on the link to the time they arrive on your site, two big reasons are
   • Server redirects – This happens a lot with ad serving. Suppose you buy an ad though a 3rd party company who then uses an ad network to place your ads on a publishers site e.g. yahoo, each party does some processing and redirect of its own. In doing all these redirects the referring information is lost or shows one of the sites that does the redirect. For example, you might see atdmt.com showing up in the referring sites which means you were serving ad via Atlas even though the ad might have been served on MSN.com. Many URL shortening services used on twitter also show up as referring domain instead of twitter.
   • 3rd Party Apps – This is a big issue with Twitter URLs. A lot of twitter users use 3rd party apps and any clicks to your URL posted on twitter from these 3rd party apps will show up as direct traffic.

   If you are running a campaign or posting links in social media, blogs, forums etc, make sure to tag them with campaign identifiers so that you can use campaign reports instead of relying on referring sites report.

Thoughts? Comments?

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
• Landing Page Optimization Analyst at Red Ventures Armed Forces – Europe

Should you use a compound metrics in your web analytics reporting? This was a topic of discussion in one of my classes at UBC Web Analytics course.

What is a Compound Metrics?

Before we get into answering the question, let’s look at what a compound metrics is.
Simply stated a compound metrics is when you take two or more simple measures and combine them together to form one metrics.

So should you use it?

Short answer is – why not? Sometimes simple metrics such, such as visits, page views, clicks etc., are not enough to explain a complex concept and that’s when you need a compound metrics, e.g. engagement metrics, visit quality measure etc.

But isn’t compound metrics hard to explain?

It depends on how you define it but then a lot of people still struggle with
visits, visitors, hits and pageviews. With that in mind, I agree that initially it might be a little hard to grasp the compound metrics. Over long term, compound metrics actually helps simplify the measurement of a complex concept.

Some of the common uses of the compound metrics are

1. Credit Score (Everybody has one and it affects them every day but how many actually know how it is calculated?)
2. Google Page Rank
3. Twitter Resonance (it will use several factors such as retweets, clicks on links etc.)
4. Twitter measurement. Many twitter measurement tools use compound metrics since it is not easy to explain Reach, Impact, Engagement in simple metrics.
5. Facebook’s “Likeability Index”. Ok, I made this one up but I am sure that’s coming soon.

Example

Let’s look at an example and see where such a metrics will make sense in your current web analytics reporting.

Lets take an example of a product information site. The products are sold offline via 3rd party retailers and since this company does not want to compete with its retailers it doesn’t sell anything online. This site provides information about the various products that this company sells. It provide white papers with pre-purchase information and post purchase information/support. The site has some videos and some stories that are published every now and then. Well there is a sign-up form to allow users to save their product information.

The whole goal of the site is to provide information to current and future customers.

Now your big boss asks “We spent thousands of dollars to build this site, is this site working?”.

You reply, well… Visits are down but repeat visits are up so seems like people like it and are coming back. However, page views/visit are down. More white papers are downloaded as compared to last month. However, video views are down and sign ups are also down. Seems like some things are up and some things are down.

Boss goes….”What does that mean? Is it working or is it not? Are customers finding information?”

How do you measure that?

As an analyst you can look at all the metrics and come to a conclusion but you have to be able to convey the end result to the VP of marketing. He needs to know if the site is successful or not.

This is where a compounded metrics comes in handy.

A simple formula for this could be

(% of visits viewing X pages or more + % of visits viewing video + % of visits downloading white papers type 1 + % of visits downloading white papers type 2)/4

we used 4 in the denominator because we are using 4 different metrics with equal weight

Now you can add other metrics that matter to the business and also assign different weight to each, so your formula could be something like:

(1*% of visits viewing X pages or more + 4*% of visits viewing video + 1*% of visits downloading white papers type 1 + 2*% of visits downloading white papers type 2)/8

1,4,1 and 2 are the weights assigned to each metrics based on their importance to the business.

Once you develop a baseline for your metrics, you can confidentially tell you boss if the sites performance is better or worse than the last month. Keep in mind that you are an analysts and you should always get under the hood to analyze each component and find opportunities for improvement.

What do you think?

Questions? Comments?

Other articles on similar topics are

• http://www.juiceanalytics.com/writing/franken-measuresor-how-construct-useful-composite-/
• http://www.usca.edu/polisci/apls301/compound.htm

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
• Landing Page Optimization Analyst at Red Ventures Armed Forces – Europe