According to Adverity’s latest research, 61% of marketing teams aim to achieve predictive analytics in 2022. However, whilst many marketers are looking to implement this into their martech stacks, the majority aren’t ready to take the next step.
More than half (56%) of marketers are still building their marketing reports using spreadsheets, despite the fact that business intelligence (BI) tools and data dashboards offer much more effective and accurate marketing reporting. Almost two-fifths of marketers who plan to use predictive analytics state they are still struggling with manual data wrangling.
However, it is not just about what platforms marketers are using to pull their reports; what is most worrying for marketers is that only 43% have access to a centralised data warehouse, making it difficult to locate and access accurate data for reports. It is no surprise that there is still a significant trust issue when it comes to marketing data. Nearly half of marketers who plan to introduce predictive analytics in 2022 don’t trust their data.
Current data capabilities
Diving deeper across the board, these issues plague all marketers; it is not limited to just one industry. However, there are some verticals that are hit harder by these challenges. Only half of ecommerce marketers have access to centralised data platforms, falling to just 37% of telecoms marketers.
Marketers are still wasting huge amounts of time and effort cleaning and combining data from multiple sources into a spreadsheet. Ecommerce is leading the way when it comes to using BI tools to visualise their marketing data (75%), however the media industry is seriously underperforming (43%).
Currently, many marketers don’t have the correct tools and processes in place to start implementing predictive analytics.
While it’s not impossible to implement predictive analytics when you are still manually wrangling data or reporting from spreadsheets, the time and wastage of resources makes it vastly uneconomical, especially as the complexity and number of data sources for marketers grows on a day-by-day basis.
What marketers need to do now
First and foremost, marketers need to start bridging the gap between their teams and their marketing data analysts. Currently, there is a big divide between data analysts and marketers around their true capabilities and what technologies they already have in place: 64% of analysts say they use a BI tool to visualise their marketing data; only 47% of marketers agree. But, by far, the biggest disagreement between analysts and marketers is on whether they have access to predictive analytics. Although 60% of analysts say they have predictive analytics, only 42% of marketers agree.
There is an easy path to achieving data maturity; it starts with getting rid of manual data wrangling and reporting on spreadsheets. Once marketers have achieved this, not only will they improve the quality of their data, they’ll also then be able to implement additional layers into their martech stacks, such as BI tools, real-time analytics and end-to-end reporting.
Before marketing teams charge ahead with more advanced analytics, they need to take stock of their current tech stack and consider this gap. Is there tech here that isn’t having a practical impact – and why might that be? Whether it’s a miscommunication, a problem with adoption, or a lack of tools and time to get accurate data, all of these issues will continue to crop up and cause bigger problems as you add in more tech.
Technology is not a silver bullet that will solve all marketers’ data queries. As the old adage goes, garbage in, garbage out. If your data isn’t accurate, the insights you get from it could end up doing more harm than good. In short, if you’re using predictive analytics without streamlined data integration, a single source of truth isn’t sustainable – especially if you want to factor predictive analytics into your long-term strategy.
The increase in marketing budgets provides marketers with an opportunity to reset and take stock. The time has to be now, otherwise marketers are going to continue spending large amounts of budget without the insights required to justify their decision making.