Having a data-driven business can ensure you stay competitive and maximise your marketing spend. But this 2020 web analytics survey by ObservePoint highlighted just how low trust levels are, with only 12% of respondents saying their data is at least 90% accurate. And if you thought that this finding doesn’t come with a significant business impact – think again.
Let’s face it – without trust in data, businesses will make poorly-informed decisions. Analytics specialists are at risk of being increasingly demotivated by low confidence and pressure from various business divisions. Without data, there is a risk that more assumptions will be made, or even worse: insights will be given based on how well-received they might be. When it comes to growing your website conversions, the last thing you need is a team of yes-men.
[Free Guide] Our data-driven framework for getting clarity and sales
In this post, I’ll be delving into where these low trust levels could be coming from and what can be done to have more confidence in your data. And the solutions go beyond simply investing more money into data.
Google Analytics is the most popular tool across the board
ObservePoint’s 2020 Digital Analytics and Governance Report focused on mapping a range of digital teams’ make-ups. It specifically showed the ways their website analytics function supported other online marketing activities. The report collected 700 responses from marketers and website analysts at varying levels of seniority and in different industries.
Most prominent sectors included in the survey were Information & Communication Technology, Retail & Consumer Products and Marketing & Communications. Not insignificant were also Advertising, Arts & Media, Healthcare & Medical, Banking & Financial Services, Consulting & Strategy, Manufacturing, Transport & Logistics, Education & Training and Hospitality & Tourism.
Nearly 40% of companies that took part were large enterprises with over 2,500 employees. The rest of the businesses were small and medium size businesses of varying sizes.
The survey also asked about the primary tools used for collecting website analytics. Key players were, unsurprisingly, Google Analytics – together with their “360” enterprise edition (used by 57% of respondents) and Adobe Analytics (used by 35% of respondents).
Google Analytics covers a wide range of spectrum in terms of the sizes of companies who use it. It has a universal appeal and low entry costs. Adobe Analytics tends to be used by large enterprises – 75% of its users in the survey had at least 1,000 employees. The report didn’t map confidence levels across the tools used – but it’s still valuable to know that the vast majority of respondents work with Google Analytics. This means that report findings relate to this tool to great extent.
Key conversion tracking is not robust
Nearly 35% of respondents identified making a purchase as their key website goal. This was followed by: contacting their company, consuming content and subscribing to or purchasing a service.
When comparing how tracking for those key conversions are implemented, 31.78% confirmed that they track the full funnel. This statistic, combined with low levels of data accuracy perception, point to the fact that data maturity levels are low in most companies.
Ensuring data is tracked correctly in all pages of your website by implementing the required code effectively is one thing. Configuring your platform is an additional, and essential, step to making sure your data is not only correct but also relevant. Without the right filters, settings, events and goals configured, web analytics data is of little value.
If being data-driven is an important aspiration for the companies surveyed, businesses across all sectors and sizes are still struggling to accomplish this goal.
Website analytics confidence gaps between marketers and analysts
The survey asked about participants’ confidence in their analytics data. 100% data accuracy is a nice target to have – but it’s not realistically achievable. To be certain of the marketing decisions you make, your analytics data should be around 95% accurate (e.g. when measuring Google Analytics Ecommerce data and the transaction data in your sales platform). Unfortunately, on average, as much as 88% of respondents said they didn’t trust their data was at least 90% accurate.
In addition to that, the survey revealed another layer to the perception of data accuracy. There is a clear misalignment in confidence between digital marketers and data analysts.
Website analysts, who are naturally closer to the data than anyone else, were more likely to have confidence in data. Around 14% trusted their data was 90-100% accurate.
In the opposite corner, only 6% of marketers trusted their data to be at least 90% accurate.
In addition, looking at how the results are plotted across all confidence levels, marketers’ trust degrees were more spread out across the board, where analysts’ perception was grouped towards the higher end of the scale. It probably comes as no surprise that website data analysts and marketing managers are cut from a different cloth – and this study revealed the scale of the gap. Worryingly, if marketers don’t trust the analysts’ data, they may not trust their recommendations either.
Analysts are the ‘ones on the ground’ – they best understand data and its flaws. However, their judgements on its reliability are not being communicated to the marketers. There are a few possible reasons for the relationship breakdown.
One explanation could be down to how the question was posed to the participants. By asking them to judge data accuracy on a 10-point scale without any position of reference, this could potentially lead to some arbitrary estimates.
Secondly, analysts may generally be more inclined to be more data-driven, and so, more trusting of the data that they work with every day. They would know with more precision which elements of company data may be inaccurate.
Marketers, who are more likely to interact with data after it’s been manipulated into reports, could be more sceptical by not fully understanding data collection methods. They might also consider web analytics an ‘add-on’ to a wider marketing strategy. Traditionally, marketing is seen as a creative function and being data-driven is a comparatively new approach. If marketers represent this attitude, they might not have provided the required resources to configure website analytics, and so, they are also less trusting of its accuracy and the value it can provide.
Finally, analysts can sometimes be a little guilty of focusing on the analytics process in their communication, where marketers are looking for concrete conclusions and recommendations. They are perceived as numbers-obsessed ‘geeks’ and their key conclusions can feel lost between describing measurement models and quoting metrics uncovered along the way.
All these factors could impact differences in data perception, but the most undeniably concerning finding of the survey is just how low data maturity is overall.
Will more investment in web analytics help increase data accuracy?
ObservePoint suggest that increased analytics testing can propel data maturity in businesses. While it will definitely help to quickly spot errors in code implementation, it will not resolve issues around not tracking interactions, goals and Ecommerce transactions in the first place. To do that, you need to invest into setting up the right configuration that helps you measure your website performance against your business goals.
However, I’d argue that lack of data configuration or accuracy is a symptom of a wider problem that needs to be resolved in the first instance. Companies should care more about what value good, meaningful data can bring – and what threats lie with using wrong data for business-critical analysis. Without this understanding, investments in data can be misplaced and not received favourably by wider teams.
It makes sense to investigate how the importance of data can be communicated within marketing and wider businesses.
Data visualisation can help bridge the analytics gap
The trend that emerged in the past decade or so to base more and more marketing decisions on data puts pressure on both marketers and analysts to deliver tangible results.
Both marketers and analysts need to take ownership of improving the accuracy of their data. Marketers should be more open when it comes to sharing business goals and removing potential barriers and silos that may exist between departments. Analysts need to become experts at showing value in what they do by sharing actionable recommendations that can significantly impact business results.
If analysts can display the potential of their findings within their business context, companies might find more resources to support their activities.
To clearly communicate web analytics insights, it could help to present data in a visually compelling way. Visualisation tools such as Google Data Studio are helpful in getting all business stakeholders to understand data.
Depending on the circumstances, maps, flow charts, area charts, bar charts, bullets, donuts and histograms are all useful. By demonstrating comparisons, trends, relationships and distributions, these visualisations can help marketers understand what data means and the hidden opportunities within.
Through releasing charts, explaining what they mean and providing justifiable recommendations, analysts can force a deeper conversation with marketers about data.
How will the 2020 web analytics survey impact your web analytics activities?
If you’re already investing is SEO or Search Engine Marketing, you need an effective way of assessing the impact of these activities. You can’t optimise your website for sales without the right web analytics in place.
What’s more, web analytics is a ‘continuous improvement’ process, as opposed to something you can ‘set and forget’. As your business grows and your website changes, web analytics needs to be tested and updated to ensure that you are getting the data you need to increase your overall ROI.
To maximise your marketing efforts, why not invest in developing a company-wide data strategy. It will help eliminate data silos and let different business functions communicate with one another by focusing on common goals.
As part of this, consider performing regular data audits to ensure your numbers are accurate and always capturing activities that are relevant to your business goals.
If you’d like to be more confident with your website data, why not start with a Google Analytics Health Check? It will highlight the key areas where you need to improve to get better return on your CRO investment.