Why Do I have a Business Website and How is it Doing? Part 4:
Taking Action-What Do I Do With All This Data?

This is the final post in the four part series: Why do I Have a Business Website and How is it Doing? The first post expressed the importance of defining clear goals for your website, the second post showed you how to assign a dollar value to those website goals, the third post explained how to create Key Performance Indicators (KPI's) to measure the performance of these website goals, and this final post will show you how to organize and look at these KPI's to make real data-driven decisions.

Most people cringe at the idea of looking over a pile web analytics reports full of numbers, percentages, and endless graphs. Often times dashboards and reports leave us overwhelmed and more confused than we were before we looked at them. The secret to effectively measuring your website's performance through web analytics data is to only look at reports that actually help you make decisions.

The KPI's you defined for your website after reading my last post is a great first step to getting your hands on helpful reporting, but it's only the beginning. You still need to look at these KPI's in such a way as to answer specific business questions, allowing you to take decisive data-driven action. The best way to go about this is to clearly define the question(s) your asking before setting out to find answers. Obvious right? And yet many of us are guilty of putting the answers before the questions thus getting a pile of meaningless data that we don't care about.

In the examples below I will highlight my 4 favorite types of reports that I've found to be most helpful to me in my web analytics reporting. For each of these reports I will define the purpose of the report, present a sample business question that would lead to a need for each report, show a sample of what the report might look like using fictitious data, and give a brief interpretation of the sample data.

4 Key Web Analytics Reports
1. Conversion Funnels
2. Distribution
3. Trends
4. Top 10 Lists

1. Conversion Funnels - this report is designed to show you how visitors follow a designated path. The first step is to clearly define that path starting with your website goal and working backwards defining each key step along the way to that goal.

*Key Business Question - How well does my e-commerce website performs in getting visitors to complete the goal of ordering products?

The Conversion Funnel below shows me the data I need to answer this question. Since every step in this funnel is required to get to the next step, the numbers from step to step will never increase and will most likely decrease - hence the funnel process. By looking at the conversion rate (% of visitors who successfully moved along the conversion path from the previous step) or the reciprocal fallout rate (% of visitors from the previous step who failed to move on to the next step) you can quickly assess how the funnel is doing overall and at each critical step. In this hypothetical example my eye is drawn to the overall conversion rate of 1.7%, and knowing that the average e-commerce conversion rate is roughly 2% I would look at ways to increase this. My eye is also drawn to the Order Complete step which loses 25% of the visitors from the Payment step - maybe there are tests I could run to convince shoppers to follow through in completing their orders at this critical step (e.g., improved security reassurance, privacy policy, guarantee policy, etc.). This is the kind of report I would want to look at regularly, comparing the conversion rates over time especially when I make a significant change to my website or shopping cart functionality.

2. Distribution Analysis - this report shows me information in pie-chart like form and can be adapted to represent many different kinds of data. If you ever want to see a breakdown of where things are coming from, this is the analysis you want.

*Key Business Question - Where does most of my website traffic come from, where do most of my website leads come from, and where is most of my marketing budget going? (Note: Conversion Rate and Cost Per Lead aren't directly related to all distribution analysis, but I thought they were useful KPI's to see in this example).

This report tells me a lot - so powerful! A few of the many actionable observations I could make from this data are (in no specific order):

• I need to relook at my paid directory investments as they have the lowest conversion rate, are costing me $108 per lead, and they are eating up 4% of my marketing budget.
• Referring websites make up 4% of my acquired leads with minimal traffic, I'm going to dig deeper here to find which website(s) is giving me such highly converting traffic - maybe I can negotiate some additional advertising through them.
• 53% of my marketing budget is going toward email but it costs me more than 3 times as much money to acquire a lead through email as opposed to Paid Search - maybe I will cut back on my email costs and put those dollars into PPC.
• Misc. traffic sources is low volume but the conversion rate is 13%, I will check within this category to see what specific source is driving those lead conversions.

Note: this example is showing a distribution analysis of traffic sources, but this kind of report can be used to look at many different things such as paid search keywords, e-commerce products, landing pages, etc.

3. Trends - a trending report is designed to show performance over time and it should clearly display the overall trend and provide a benchmark with which to measure the data against. I tend to like to use the historic average as my benchmark in most cases unless I have a different reference such as a goal or an industry average. Graphs are a great way to display this kind of analysis for a few key metrics.

*Key Business Question - Since the start of 2009 has my website traffic and orders been increasing or decreasing?

In the example below I am showing a trend analysis for Visits and another for Orders. In each graph I have each month's data shown as blue columns, the historic average shown as a flat red line, and the green linear trend showing if the displayed time frame is showing an increase or decrease (the steepness or flatness of the trendline's slope quickly shows me how drastic the trend is). Comparing the two graphs below I scan for the outliers and I compare the two trendlines. The outliers will appear as blue bars (i.e., months) that fall well above or below the red line (average). If I see an outlier that seems strange it alerts me to investigate further. For instance I see that May and June had record visits but close to average orders which tells me that this extra traffic isn't converting (hope I'm not paying for that extra traffic), and I see that April had the lowest orders of all so I would look into possible causes. After outliers I quickly compare the trendlines - in this case traffic is increasing at a significant rate but orders are more flat, only slightly increasing. This tells me that I'm getting more traffic but it's not quality, converting traffic.


4. Top Ten Lists - there's nothing too profound to share about top 10 list analysis other than to stress the importance of them. In web analytics it's very easy to get overwhelmed with the sheer volume of things to look at. You might be looking at a landing page report with hundreds of specific landing pages or a list of thousands of referring keywords. The key to actionably analyzing huge volumes of data is to sort it by volume and only look at the top 10 or 20. This concept relies greatly on the 80/20 rule, and by focusing your attention on the most important 10 or 20 things you will be able to take action on the things that have the greatest impact.

*Key Business Question - I am running PPC for my chess website designed to acquire leads, how are my keywords performing and am I putting my money into the right keywords?

The below example shows the power of a top 10 analysis in action. For this example I have added some distribution data as well (described above) to quickly show me where my traffic and leads are coming from and where my advertising costs are being invested. I have also added a cost per lead column to quickly show me how much a lead costs me for each keyword. We'll assume in this example that I've determined that a lead is only worth $24 to me, so my break even cost per lead is $24 (anything greater than that indicates an unprofitable keyword). From this data I can quickly see that combined my top 10 keywords make up 70% of my total PPC traffic, 87% of my total leads, and are consuming 82% of my advertising budget. My top 3 most expensive keywords alone make up half of my total advertising cost while only representing 32% of my total leads, and since the top 2 are losing money with Cost-Per-Leads of well over my $24 break-even, this is a big problem. The 4th most expensive keyword, "chess software", is a big loser and is wasting 9% of my budget - I will pause that keyword immediately. As you can see, by isolating my top 10 keywords I'm able to make quick decisions on just a few important keywords that will have more impact than making hundreds of similar changes to less significant keywords. This kind of analysis can be extremely helpful in many situations where you have a sea of data and you feel the 80/20 rule is applicable.

Key Takeaway - The key to powerful analytics is to start by asking specific questions about your business goals. Only after you've clearly defined your question should you begin gathering and analyzing data. Make sure you organize your data in a way that makes it easy and obvious for you to analyze and make data-driven decisions. If you look at a dashboard or report and say "so what, who cares, I'm confused..." - delete it and come up with something that will actually help you take action. Four types of reports that can be very helpful in analyzing web analytics data are: conversion funnels, distribution, trends, and top 10 list analysis.

Conclusion:
I hope this series has helped you understand what all goes into measuring the performance of your business website. The four steps you need to take are:
1. Define your goals
2. Monetize your goals
3. Define KPI's relating to your goals
4. Organize your KPI's so you can easily analyze them and take action!