Almost everyone already understands the usefulness of web analytics.

It’s part of the standard online toolkit companies around the world use every day. But, are they getting the most value out of their analytics?

On the surface, web analytics give you a great deal of fascinating data about your users. But if you don’t progress past the dashboards and topline reports and start mining data using segments and the analytics APIs in a way that is relevant to your customers, you are missing out on surfacing insights that drive consumer strategy and can impact operational decisions.

This task – transforming user data into a meaningful action plan – is what separates casual users of analytics platforms from marketing industry users of analytics. Whilst useful, there is much more to web analytics than reporting, measurement, and conversion optimisation.

What Story Are Performance Indicators Really Telling?

One of the most useful and intuitive ways to approach analytics is to imagine the data tells a story – put your customer at the centre of the narrative, with the final moment in the story the desired outcome, and patterns in the data and interactions with website functionality representing crucial moments along the way. It is those moments you want to focus on during analysis, paying particular attention to how those moments relate to conversion.

For example, we know we have a customer base at the start, and we know how many make it to the end, however it’s the bits in between that help us improve. We do this by asking questions between the start and finish such as, “what proportion of those customers watched a video at the start?”, “did these users convert after watching a video?”, and “are users more or less likely to convert having watched a video?” The twist in the story might be finding out your video is actually driving users away! Until we ask these stories we’re flying blind in terms of understanding the customer’s narrative.

Phil Green, author of misLeading Indicators: How to Reliably Measure Your Business, warns that when measuring business performance, the numbers simply can’t tell the whole story themselves. This is as true with opinion polls and corporate risk metrics as it is with web analytics data.

Analytics and benchmarking audits are designed to take onboard these scenarios and stories from wider teams, and identify patterns in web analytics data to help focus strategic direction.

Case Study – Benchmarking Audit of P&O Cruises

To showcase how benchmarking audits can derive value from Google’s web analytics data, let’s examine how Deepend helped P&O Cruises maximise occupancy and ticket sale profit for its cruise line-up.

A key story was to focus analysis on customers’ interactions with specific cruises and map how their interactions with that cruise page changed based on the number of days before it departed. Lead time behaviours identified patterns which helped recommend messaging at key milestones prior to departure, as opposed to a static message throughout the cruise page’s lifecycle.

We then built dashboards for every cruise within the P&O schedule, where we noticed those lead times and behaviours changed significantly by cruise type and length.

Some cruises were consistently being booked up to a year in advance, while others filled up only a few short weeks before the departure date, if they filled up at all – it was mapping the content viewed by lead time that really helped understand the customer and what drove these behaviours.

Our benchmarking audit provided the data we needed to form a comparison between these cruises. What were the differences between them, and how could P&O Cruises solidify their presence in the tourism industry using this data?

Linking Figures to Customer Behaviours

The eureka moment didn’t come from the numbers themselves, because the numbers can never tell the whole story. It was by understanding how those numbers fit into customer behaviours and attitudes that we were able to help the company shape its pricing and yield strategy and generate improvement in ticket sales across the board.

What we found was that the numbers coincided with a general sentiment Australians have – that South Pacific cruises are plentiful and can therefore be planned reasonably close to the departure date. It was only cruises connected to special events, like the Melbourne Cup, that saw bookings sell out far in advance.

Australians’ purchase behaviours are entirely different depending on the length and destination of individual cruises. As a result, the pricing strategy P&O Cruises uses to sell tickets for upcoming trips has to accommodate its customers’ expectations.

Our reporting suggested that making changes to the yield strategies of individual cruise lines based on the factors customers care about would massively increase the profitability of cruises across the range.

This insight – a cultural attitude shared by a majority of Australian cruise ship passengers and expressed in figures available through Google’s Web Analytics – inspired P&O Cruises to overhaul its yield strategy. Instead of trying to push unprofitable cruise lines to potential passengers, the company could now focus more resources on established patterns in customer behaviour.

Consequently, the company changed its approach to media planning and gave priority to promoting cruises that aligned with customer expectations. As a result, occupancy surged – and so did profits.

Are you ready to dive into your web analytics data to glean insights on customers’ online purchasing behaviour? Contact Deepend’s marketing technology experts to find out more.

Find out more about driving online performance through website analytics and CRO to help better understand the data collected through your website.