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How to Get the Most Out of Your Web Analytics Tools

Here we look at the common practical issues in “getting analytics to work”. Based on our experience, we look at pragmatic steps that can be taken to resolve thes…

Web analytics tools are ultimately only a means to an end. Organisations need answers to critical questions:

What marketing and content works (and doesn't work)?

How do customers engage online?

Where are the opportunities to add value?

To answer these vital questions we need to bridge the gap between the complexities of online data and the need for concise analysis.

Here we look at the common practical issues in “getting analytics to work”. Based on our experience, we look at pragmatic steps that can be taken to resolve these and start to unlock the real potential of the technology.

1. Get a high level analytics strategy in place from the start that summarises your key business questions.

An analytics strategy sets out in simple language the high-level questions that the business needs to get to grips with, in order of priority.

For example, the key questions for a retailer might be:

What is the true cost of acquiring a new customer online?

What investment in content is most likely to engage visitors profitably?

Where do my most valuable customers actually come from and where can I find more of them?

The brief for the service provider is then “How will you help us answer these questions?”

2. Be disciplined in choosing KPIs and challenge the assumptions used in the process.

It's all too easy to get focused on one metric that doesn't actually represent real economic value.

For example, retailers with impulse-buy products might favour “average revenue per visit” as a better site performance metric than conversion rate.

The process of choosing KPIs based on real business objectives (e.g. profit) is vital, and needs to challenge assumptions at every stage.

3. Don't try to complete tool implementation in one, final cycle.

An iterative approach is far more likely to get good results on time and avoid a seemingly never-ending quest to get the deployment fit for purpose.

There's no golden formula for this (it's rare to find two sites with an identical technical setup), but a typical process might be:

Basic Tagging – Focus on getting site tagging across the entire site in its vanilla form.

Conversion Events – Do whatever re-tagging or customisation you need to capture the events that are most economically critical

Campaign Segmentation – Get a labelling scheme for all your off-site marketing activity Content/Engagement – Review on-site content segmentation and tagging requirements for grouping content and tracking engagement events.

4. “Accuracy” should be focused on consistent data collection and a clear understanding of metrics.

Accuracy and trust are big issues in analytics. If the highest echelons of the organisation don't believe the figures, the whole analytics exercise can become a waste of time.

Often training for the senior management team on web metrics is the most important step to resolving the ongoing “accuracy” debate.

Then focus on making sure your deployment stays consistent when other things change.

5. “Like a rabbit in the headlights”

For every new report and every new jazzy feature in the web analytics tool, there's more information to look at.

If there’s a feeling of “drowning in data”, go back to your key questions and get professional advice on translating these into the required metrics and analysis.

6. The “web analyst” to the rescue?

Web analysts need a broad awareness of a spectrum of commercial and technical issues, with some quite niche skills such as JavaScript programming, database skills, marketing nuance, business clout as well as analytical skills. Fully-formed web analysts are in short supply, so bringing together the right combination of skills (internally and externally) as a team may be a better approach.

7. Focus your optimisation and analysis across the customer cycle

If your business is customer-centric, then making your analytics customer-centric is a great way of focusing the process. We can then wrap optimisation and analysis around the customer cycle of acquisition, retention and monetisation.

Finally, you can feed back lifetime value insights into your acquisition targeting to make sure you focus on getting the right kind of customers.

8. Don't forget the big picture of competitor and survey intelligence

Look at the key trends in context of each other rather than in isolation. Analyse the marketing and the opportunities there may be. What is and isn't working within the confines of your own site and marketing. Finally, What do your customers really think?

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