Despite continued investments in data-driven marketing, problems persist. In fact, 84% of B2C marketers surveyed by Pecan for a new report [download page] agree that despite all the customer data their company gathers, it’s still difficult to make day-to-day data-driven decisions and take action.
This has been a longstanding problem, attributed in part to data siloes and organizational issues. Not surprisingly, the B2C marketers surveyed by Pecan see great value in putting their data to use in decision-making and empowering their marketing teams to extract the most impactful analyses from their data. Yet for about half, their ability to predict customers’ behavior is always (8%) or often (41%) guesswork.
Improving these abilities will likely involve better collaboration with data science teams, per the report’s findings. The analysts write that “the causes for misalignment occur at every stage of the typical data science workflow.” Indeed, when asked what causes data projects to stop making progress towards marketing goals, marketers pointed to a variety of issues. Among the most common complaints are that those building the models don’t understand marketing’s goals (40%), that overwhelmed data scientists don’t have time to meet marketing’s requests (42%), and that data isn’t updated quickly enough to be valuable (38%).
In other highlights from the report:
- Only 28% of survey respondents said that they could adjust their acquisition and retention programs to shifts in customer behavior within a week or less.
- Some of the more popular metrics used to quantify the value of marketing analytics tool and resources are ROI on advertising spend, churn and loyalty KPI improvement, and lift in acquisition of high-value/profitable customers.
- Some 45% say it’s extremely (4%) or very (41%) challenging for their marketing team to show quantifiable ROI for campaign and channel performance. None of the respondents said it’s not challenging at all.
- More than one-third will completely (6%) cut back or cut back a great deal (31%) on planned investments in marketing technology and data measurement due to a potential economic downturn.
About the Data: The results are based on a survey of 250 US marketing executives at B2C companies that use predictive analytics and have a minimum annual revenue of $100 million.