Data driven decision-making is becoming more important in marketing. Marketers need to build their strategies based on reliable insight into which campaigns work, and which ones don’t. In order to truly engage with their customers, understanding how these customers behave while browsing websites and other digital content is key.
Ideally, data analytics needs to track a mix of digital platforms, from websites to apps and social media. It should also take into account data from a variety of sources such as the e-commerce system, CRM and marketing automation solutions.
But, collecting the right data and having the right analytics in place is easier said than done. How are insights shared across teams and departments, and how are they turned into action?
Below are seven warning signs that an organisation is not using analytics to boost its marketing:
1. Measurement isn’t part of the planning process
The marketing team can spend countless hours on developing content, planning product launches, and setting up new advertising campaigns. However, if a discussion on how to measure success with data isn’t part of the initial planning, the time spent on content development may well be wasted.
Data driven marketing requires a culture of measurement. Measurement should always be part of the conversation, to lay the foundation for future success.
This includes identifying the areas to measure that will provide the most insight and value, defining what is most important to the business and considering where decisions are being made without data. Benchmarks should be set based on past performance and goals defined accordingly.
Given a big chunk of the marketing budget is usually spent on campaigns, measuring campaign success has to be a focus. Tracking codes on URLs allow organisations to more closely follow their customers and prospects along their journey to the website.
2. People in the organisation don’t trust the numbers
According to a recent Experian Data Quality study, 81 percent of companies believe data is essential to their marketing success, but a staggering 84 percent of organisations reported problems with data quality. The most important learnings from the data will not translate into actions if a company doesn’t trust the accuracy of its own data analytics.
To boost trust in the data, the marketing team should have a validation process in place that ensures they are collecting the right data to answer important business questions. Points to consider include whether the company’s website is tagged properly to yield the right measurements.
There is no such thing as 100 percent perfect data, but there should be an agreed standard for data accuracy. When critical metrics are identified, it’s important to always compare like with like. There is no point in comparing results between different tools such as a web analytics solution and a marketing automation platform, for example.
Data and analytics literacy is equally important and the marketing team should have access to relevant training. A report that is created using the wrong metrics or date range may look like the data isn’t accurate when it’s actually the setup of the report that is incorrect.
3. The team is only monitoring traffic and page views
Data driven marketers need to pay attention to the metrics that really matter. Page views aren’t everything – often, it’s the conversion rate that ultimately counts. Who cares if a new campaign drove a 30 percent increase in traffic, if the conversions are down by 5 percent?
To identify which metrics should be monitored, it’s important to ask the right questions about the business. What are key indicators that the business is doing well? This could be profit, margin, marketing leads or ROI, to name a few. The best tactic is to pick those that really matter and then work out how to use analytics to monitor them.
For example, A/B testing helps understand which experiences are really engaging the target audience. Looking at the flow of visitors to the different digital platforms, knowing where they have come from, and comparing the traffic with the bottom line results allows an organisation to identify any issues or untapped opportunities.
4. Everyone sees the same data
Different stakeholders in the organisation will need access to different sets of data. Marketing managers should have one view to help them measure and understand day-to-day results for their programmes and campaigns, while senior executives would likely prefer a roll-up, high-level dashboard that demonstrates business results.
To provide real value, the data has to be meaningful to the internal audience and presented in the right way. Dashboards and reports should always be personalised when presenting analytics data to key stakeholders. Data visualisation tools help keep reports relevant.
5. Difficulty answering questions on the fly
If a report brings up more questions than answers, it’s a sure sign that further analysis is required. Unexpected behaviours or anomalies in the data need to be investigated by drilling down deeper.
Ad hoc analysis tools can be used to gather more data than a snapshot report, and provide the insight needed to adjust campaigns or customer experiences. Ad hoc data exploration can provide insights such as specific details about the visitors exhibiting interesting behaviours – looking at geographies, devices used, etc. They can also help find the common thread – this could be a certain period of time, a customer segment, or content.
6. There’s no analytics training for new employees
While employee turnover is inevitable, losing the person who has the majority of the company’s analytics knowledge is a major setback if they can’t be replaced quickly.
There should always be a backup analytics expert in place, with both analysts and end users properly trained on the analytics technology as well as internal processes and governance. Formal documentation and governance of report and dashboard organisation, roles and data access permissions, integration with other data sources and analysis tools, and tag structure will all help with smooth training. There are certification programmes available for analytics proficiency.
7. The company is not making decisions based on the data insights
Reports are important but they are meaningless if they don’t translate into action. The real value in analytics is when it’s a catalyst for positive business change. An organisation that merely collects and analyses data without communicating insights and recommendations is wasting valuable time, resources and opportunities.
Solid governance of the analytics programme is key, defining roles, responsibilities and processes. Letting the data tell a story, explaining what the data reveals will identify real opportunities for change. A company that implements a culture of consistent testing, hypothesizing and applying learnings is a company more likely to succeed.
