Analytics Deep Dive Part Two: How to create a meaningful measurement model
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Analytics Deep Dive Part Two: How to create a meaningful measurement model

Author: Aditya Khanna | Categories: Digital Analytics, Digital Marketing, Google Analytics

Note from the author: First of all, I would like to thank you all for loving Part One of my Analytics Deep Dive series, Why Traditional Page Analytics Fail to Provide True Business Insights to Professional Firms. Because of your interest, this was our top blog for April and the #4 blog in May! Also, I appreciate your patience waiting a month for Part Two – we have been crazy here – but I am happy to say it’s finally here!

Visitor engagement is a powerful metric that can help organizations understand their audience and investment in any online/offline channel – at least it can if it’s done correctly. The challenge for organizations looking for insight into their marketing efforts, however, is how best to approach their digital data?

Measuring engagement requires a lot of time and effort to get right. You need a plan your strategy, garner executive buy –in and pin down concrete metrics to track and revisit. In this article, we will walk through our process to establish key analytics goals to track and assess your campaign success.

What is “Good Data?”

Good data is the foundation for making smart decisions. Having the right information, and a process to consistently measure it is the only way to distil good insights from your marketing efforts.

But, how do you define what “good data” means? The simple answer is that you want to make sure to track information that aligns with your business objectives. There is a golden rule in business that you manage what you measure.

While many different analysts may track a variety of different data points, they key is to make sure your database processes are aligned with your business strategy, and that your team is pulling in the right information to offer insight. At a very simple level, if you want to know the effectiveness of your email campaigns, you will need to know open rates, click through rates, etc.

Decide What Numbers Matter

For most organizations, gathering good data is a strategy problem, and not a technology issue. Most companies have some kind of tool pulling in analytic data – common ones include Google, Sitecore DMS, Web Trends, Adobe Marketing Cloud/Omniture – but they really have no idea what to collect.

Each organization has different set of objectives, goals and personas and that means that every organization will have their own unique measurement model, but every digital analytics dashboard should cover three major buckets:

  1. Acquisition: What channel for traffic or channel where you are spending your marketing budget?
  2. Behavior: What action you want visitors to take?
  3. Outcome: What do you count as conversion?

As you develop your analytics models, make sure each it reflects each of these three critical analysis elements – or rework on your measurement model until it does.

It Takes a Team

No tool in this world can give you data can work without insight. It is people who decide what data matters, and what doesn’t, and who make your tools work to impact your business needs. Make sure you have effectively staffed your team with the skill sets required to manage your analytics processes, and then take the time to set up the right kinds of goals.

I have seen many analytics professionals focusing on analytics implementation rather than analytics measurement model, but this is a flawed approach. As a rule of thumb, we always recommend nearly the opposite – that you spend 10% of your analytics budget in tools and 90% in resources.

Who to Approach?

You want to make sure to include key decision-makers in your data analysis process. For product managers, make sure your VP of Marketing or CMO is involved in your analytics discussions – and if you are the CMO, make sure your goals have been vetted by your C-Suite.

Getting the right parties involved in the process ensures you will create an effective measurement model based on numbers that are relevant to your executive team – the final arbiter of your team’s success.

How to Create a Measurement Model?

There are 5 key components of analytics measurement model:

  1. Objective
  2. Goals for Objectives
  3. KPI’s for Each Goal; Targets for Each KPI
  4. Segments

Let’s walk through a detailed way to think about each of these components:

  1. Objective: What are you trying to accomplish?

When we are talking about objective in analytics you are talking about today’s concrete goals, and not a theoretical goal you want to achieve five or six years from now. Further, your objective has to be aligned with your current marketing strategy.

That means that you may have a long-term objective to improve your overall brand look and feel. However, if your marketing team is not doing anything to currently address your approach to branding, then you can’t consider it a current objective.

For example: the VP marketing of a Law Firm may have the following three objectives:

  1. Branding
  2. Generate Leads
  3. Improve User Experience

This measurement process doesn’t need to be difficult. While some core analytics tools will allow you to set up dashboards, you can also create a simple table in excel – which you can always open and modify as you learn more.

Objectives Branding Generate Leads Improve User Experience
  1. Goals: How do you plan to accomplish your objective?

Your goals talk about how what specific elements of your overall objective you will use to accomplish these objectives, such as the channel or strategy you will leverage. Since each of your objectives are independent of each other, you may or may not have different goals associated with each one.

Using our law firm example, perhaps you decide that under improving general branding, you would like to see more people search your company using your brand name. As a result, you would list the goal as: Improve brand visits using online and offline media like billboards, newspaper advertisements, banner ad’s etc.

Here is how we would set up goals for each objective:

Objectives Branding Generate Leads Improve User Experience
Goals Improve organic brand visits using online and offline media. Content marketing Videos
  1. KPI’s and Targets: What Data Will You Track?

Once you set up your objectives and goals, you need to specify which key performance indicators and targets you will use for each goal. These KPIs will be used to measure the performance of our goals.

In our law firm example, the KPIs and targets would look like this:

Objectives Branding Generate Leads Improve User Experience
Goals Improve organic brand visits using online and offline media. Content marketing Videos
KPI’s Branded keywords traffic Downloads
Contact forms completed
Views
Targets 5000/Month 50 Downloads
5 Contact forms completed
50 views
  1. Segments: What data elements do you need to track?

Your data collection segments are the dimensions and metrics you need to track in your analytics in order to analyze your data and find meaningful insights.

Identifying your segments will complete your measurement model, giving you a critical insight you’re your marketing where objectives, goals, KPI’s and data segments.

Objectives Branding Generate Leads Improve User Experience
Goals Improve Organic Brand Visits using online and offline media. Content Marketing Video’s
KPI’s Branded Keywords Traffic Downloads
Contact form fill-ups
Views
Targets 5000/Month 50 Downloads
5 Contact form fill-ups
50 views
Segments Visits Source/Channel Visits
Destination URL
Events
Source
Conversion
Visits
Destination URL
Source/Channel

Check Your Model

There is both an art and a science involved in deciding what data matters to your business, and a learning curve involved in perfecting your measurement strategies.

Use the tactics listed above to set up a concrete measurement model, and then revisit this model as needed over time, as your business goals and objectives evolve.

Tell us what you think: What is the hardest objective to track via analytics?

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