3 Steps to an Actionable Web Analytics Strategy

1 Comment 27 August 2012

The term “big data” is ubiquitous: in Google, the query “big data” returns 867,000,000 search results–more than Justin Bieber and Lady Gaga, combined. Despite the growing accessibility to various types of data, many marketers are still struggling to find the value in analytics. Below are several key statistics that support this prevailing perception:

  • 34% of marketers reported that analytics were not integrated at all with their business plan.
  • Less than half of analytics data collected is actually useful for decision making, according to a majority of surveyed marketers.
  • Only 11% of marketers’ customer-related decisions are driven by data, according to a CEB study. The same study claims that a majority of marketers still rely too heavily on intuition.

Clearly, creating and executing an actionable web analytics strategy is easier said than done. We all want to feel like our efforts helped to propel our business forward, but efforts cannot be quantified without understanding performance first. Below is a set of steps that guides the development of a strong digital measurement strategy.

1. Select KPIs that align to your business and digital objectives. 

Before choosing KPIs, ensure that your business and digital objectives are specific and concise. These conditions form the foundation of a strong measurement and analytics strategy. The more vague your objectives are, the more difficult it will be to identify appropriate KPIs and deliver results against them.

Once you have a good handle on your business objectives, choose the metrics that should serve as KPIs for each digital objective. The model below illustrates this concept.

measurement strategy model with business objectives, digital objectives, and key performance indicators

Consider the following basic example. Assume that you work for Company A, which sells widgets online and in stores. Your main business objective is to increase revenue. To do so, you’d like to increase revenue via digital channels. An example KPI could be revenue via digital channels.

2. Define goals for each KPI and report against them. 

KPIs need context; you should know where you’ve been and where you want to go. Benchmarks and goals anchor KPIs.

Let’s return to the Company A example. The revenue goal for this year is $10,000,000. According to Chart 1 we’ve earned $8,000,000 in revenue so far this year. With the assumption that revenue is growing at the same rate each week, we’re tracking ahead of schedule in terms of revenue.

chart with revenue to date by digital channel and progress against revenue goal

Goals can manifest in a variety of forms. Benchmarks and forecasts can guide them but in the absence of this data, a range of expected outcomes may be used instead. For example, based on variables including (but not limited to) level of competitiveness, monthly search volume, position, and quality score, we can expect a range of paid search click-through rates (CTR). Considering the range of CTRs and landing page elements,  we are able to anticipate a range of conversions via paid search.

Based on the level of sophistication, goals can also be as simple or as complex as needed. In their simplest form, goals could be target volumes (e.g. we want to earn 100 social shares on our widgets site). Or, in a more advanced form, goals could be configured as an index based on a custom algorithm (e.g. we want to earn a widget engagement index of 120 this year).

3. Use analytics to inform digital marketing decisions. 

So your KPIs are aligned to your business objectives and you’ve articulated educated and ambitious goals for these KPIs. Now it’s time to apply your understanding of performance toward making optimizations and decisions.

Generally, basic metrics can assist with making tactical decisions while more sophisticated metrics can inform strategic decisions. For example, email sign-up conversion rate could inform decisions about the layout and calls to action on the page. At a more advanced level, email sign-ups could be assigned a financial value; when this data is compared with the financial data for other conversions (or traffic sources or media channels, etc.), it can guide investment decisions.

To demonstrate, Chart 1 tells us how well we’re tracking against our revenue goal but it doesn’t tell us the full story. On Chart 1, we can see that paid search drives over half of digital revenue but it doesn’t show us the spend efficiency for each driver. Let’s direct our attention to Chart 2 below.

chart with return on ad spend by paid search and display media

In the past 6 weeks, return on ad spend (ROAS) for paid search and display has been becoming more similar. Ceteris paribus, in the future we may want to test reallocating some funds from paid search to display to understand and optimize the impact on revenue. Or, at minimum we should continue to monitor ROAS by driver to see if the pattern continues and make optimizations when more data is available. To reiterate, this is a very basic example meant for illustration only. It goes without saying that many more factors could impact a decision to test the reallocation of funds.

From a digital cross-channel perspective, the scope of web analytics should cover each area of the marketing funnel: awareness at the top, consideration and engagement in the middle, and purchase intent closer to the end of the path to purchase. This scope could include performance data from the following areas:

  • Website behavior
  • Organic search
  • Paid search
  • Social media
  • Display media
  • Blogger outreach
  • Email/CRM

The more you know about performance, the better position you are in to make strong marketing investment decisions. To make your analytics program even more meaningful, aggregate it with data from traditional channels as well.

In conclusion, narrowing your focus to metrics that correspond to business objectives, defining goals for these metrics, and using the results to make marketing decisions can ensure your web analytics strategy is actionable.


  1. KPIs vs. Metrics | Proximity Search Work - January 30, 2013

    [...] a past blog post, we covered the role of metrics and KPIs in creating an actionable  measurement [...]

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