New Survey Finds Data Science is Not Benefiting Marketers
84% of Marketing Executives Say Their Ability to Predict Customer Behavior is Guesswork
October 27, 2022
NEW YORK & TEL AVIV, Israel – October 27, 2022 – While companies tout the criticality of consumer data on a variety of fronts, from predicting future purchases to customer churn, the reality is that more than 4 out of 5 marketing executives report difficulty in making data-driven decisions despite all of the consumer data at their disposal, according to a new study of senior marketing executives by Wakefield Research for Pecan AI, the leader in AI-based Predictive analytics uses data, statistics, and machine learning techniques to build mathematical models that can generate predictions about things likely to happen in the future…. for business teams and the Business intelligence (BI) includes gathering, storing, and analyzing business data, as well as using that analysis to inform the actions of the business. analysts who support them. Surprisingly, the study also found the same number of respondents (84%) saying their ability to predict consumer behavior feels like guesswork.
Among respondents, most or all (95 percent) companies now integrate AI-powered predictive Analytics is a business practice that uses descriptive and visualization techniques to gain insight into data; those insights can then be used to guide business… into their marketing strategy, including 44 percent who have indicated that they’ve integrated AI-powered predictive analytics into their strategy completely. Among the marketing executives whose companies have completely integrated Artificial intelligence (AI) refers to the development of computerized systems that can carry out tasks and perform actions that augment or take the place of… predictive analytics into their marketing strategy, 90 percent report that it is difficult for them to make day-to-day data-driven decisions. All 250 respondents have specified that they wanted to gain additional AI-powered capabilities and predictive insights for their teams, clearly indicating that current implementations of predictive analytics are poorly serving the needs of today’s marketing teams.
“With most companies today employing manual model building approaches, it’s unfortunate, but not surprising that the results are failing the needs of marketing teams,” said Zohar Bronfman, Co-Founder and CEO of Pecan. “While data scientists may be skilled in building the perfect software models, they are simply too far removed from the nuanced realities of the business to be effective. In addition, given their workloads they are too slow to respond when considering the rapidly changing market conditions and consumer behavior. Marketers and marketing analysts are more than capable of handling predictive analytics responsibilities if provided with the right tools.”
When asked about the top obstacles in keeping data projects from progressing:
- 42 percent say data scientists don’t have the time to meet requests
- 40 percent say those building the models don’t understand marketing goals
- 38 percent of respondents say data scientists don’t ask the right questions
- 37 percent of respondents indicate that wrong or partial data is used to build models
The study also found that nearly all (93 percent) of marketing executives polled agree that data scientists could solve more complex problems if they were able to use low/no code AI predictive modeling tools for automatable metrics as future churn and lifetime value.
Among other findings, the study also revealed that today’s marketing executives need more than generalized actionable insights from their data investments. 61 percent are aiming to empower their teams to extract the most impactful analysis from our data. And importantly, not only should that information be impactful, it should also be specific to key team KPIs and readily surfaced: 60% of marketing leaders said they wanted to “uncover specific KPIs from my data instead of scouring for potentially useful insights.”
About the Wakefield Research Study
The Wakefield study polled 250 senior marketing executives with the title of director and above at B2C companies that use predictive analytics with a minimum annual revenue of $100 million.
To download a report with the full results of the survey, visit: https://www.pecan.ai/resource/state-of-predictive-analytics-marketing-2022/
About Pecan AI
Pecan helps business intelligence, operations, and revenue teams predict mission-critical outcomes. As the world’s only low-code Predictive analytics uses data, statistics, and machine learning techniques to build mathematical models that can generate predictions about things likely to happen in the future…. platform, Pecan enables companies to harness the full power of Artificial intelligence (AI) refers to the development of computerized systems that can carry out tasks and perform actions that augment or take the place of… and predictive modeling without requiring any data scientists on staff. With Pecan’s platform, companies turn hindsight into foresight by generating highly accurate predictions and recommendations that improve customer lifetime value, retention, conversion rates, Demand forecasting involves trying to determine the likely future need for an item, based on historical data and analytics showing how much of it has…, and other revenue-driving KPIs. Founded in 2018, Pecan’s predictions impact billions of dollars in revenue for fintech, insurance, retail, consumer packaged goods, mobile apps, and consumer services companies of all sizes. Learn more at www.pecan.ai.
Aircover Communications on behalf of Pecan Artificial intelligence (AI) refers to the development of computerized systems that can carry out tasks and perform actions that augment or take the place of…