For many marketers, 2022 is a year of opportunity. The latest Bellwether report says that marketing budgets are continuing to recover back to pre-pandemic levels and a positive outlook is returning.
However, while there is cause for optimism, 2022 should also be a year of review. Marketing teams should be looking at their data practices, making sure that they have the right people, the right technologies and the right attitudes towards data.
In 2022, according to Adverity's latest research, 61% of marketers plan to achieve more predictive modelling. However, almost half are unable to get a single unified view of their data. Even more damaging to marketers’ plans is that 38% of respondents who want to implement predictive analytics are still struggling with manual data integration.
Put simply, for that 38%, there is no point in even trying to run predictive analytics while still manually wrangling data. While it's not impossible, the amount of data, the complexity of it, and the time it would take to run a single model, would not be affordable. On top of the waste of resources, manual integration also increases the chances of human error. The research found that analysts who struggle with manual data integration are nearly four times as likely to struggle with low trust in data accuracy.
For predictive analytics to work as marketing teams want it to, they need to ensure that their data is all uniform and stored in one centralised warehouse or lake. The technology is not just 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, predictive analytics without an automated single source of truth isn’t sustainable, especially if you want to factor predictive analytics into your long-term strategy.
So, it should come as no surprise that those with the tools to centralise and get a single view of data are much more likely to be running predictive models.
Importance of data skills
Of the marketers and analysts we surveyed, half said they are currently using predictive analytics. What we’ve found is that these respondents are much more likely to have stronger strategic capabilities supporting a proactive marketing strategy.
For example, respondents who have strong campaign reporting capabilities are twice as likely to be using predictive analytics than the respondents who say their campaign reporting needs improvement. Similarly, marketers and analysts who are good at campaign optimisation are more than twice as likely to be using analytics.
What this tells us is that building a strong set of marketing capabilities – particularly when it comes to reporting and optimisation – will make the transition to using predictive analytics far easier.
What does this mean for agencies?
Currently, 66% of agency marketers surveyed are planning on implementing predictive analytics in 2022, with 56% planning on incorporating AI or machine learning into their analytics as well.
However, over half of agency marketers are still not able to access all their marketing data from a centralised data warehouse/data lake. Layered on top of this lack of access to a centralised data store, only 58% of agency marketers have self-service access to real-time reporting. Most shockingly, however, is that under half of agency marketers are able to track end-to-end performance of marketing campaigns.
For agencies to really thrive and embrace new technologies such as predictive analytics, they need to start by taking a step back and looking at the gaps in their strategy. Then they can fix those fundamental issues, before they start adding more into their existing tech stacks.
The increase in marketing budgets provides this opportunity to invest in the tools and people to make sure this is the number one priority. Otherwise, agencies and marketers are going to continue spending large amounts of budget without the insights required to justify their decision making. Start 2022 by getting all the practices in place and then implement predictive analytics.
While the technology is available, the first question you should ask your marketing teams is, are we really ready for it?
Looking to get your strategic priorities in order? Read the full report: Marketing Analytics State of Play 2022: Challenges and Priorities
