Envestnet® | Yodlee® Data Analytics gives you the competitive intelligence and accurate market visibility you need to make informed decisions. Predictive insight is elusive in turbulent times. Our consumer spending data analytics gives a view into broad market activity, so you can see trends as they emerge. One example is our view into this year’s Amazon Prime® Day. Results outperformed previous years, reinforcing the strong shift to online shopping in 2020.
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Rising inflation, labor shortages, and concerns over consumer spending growth are critical factors impacting both business decision-makers and investors in 2022.
With strategic tools that leverage timely and accurate consumer spending trends data, firms can identify market trends, make informed decisions, act on new opportunities, and outsmart the competition.
Sharpen investment strategy with aggregated, pre-packaged spending data analytics providing clean, accurate and ready to use KPIs.
Consumer spending data analytics from Envestnet l Yodlee can provide near real-time insights into key performance indicators like revenue, retention and loyalty, and customer churn across U.S. brands.
Consumer trend data from RVshare showed the important role RVs played in 2020. They believe demand is expected to continue through 2021. Download to read more.
Before you work with an alternative data provider, you’ll want to ensure they meet your specific requirements along with all applicable data security and privacy standards.
This eBook explores how retail and ecommerce brands should constantly be asking questions about their customers, competitors, and future opportunities.
Make strategic decisions that optimize customer lifetime value with visibility into total spend, share of spend and brand affinity.
With Envestnet | Yodlee TXN Shopping Insights, merchants can view their customer base to uncover shopping patterns, measure ROI of marketing efforts, and identify and act on growth opportunities.
As consumer habits and practices continue to evolve, traditional credit score data is no longer enough to go on when attempting to build more accurate credit risk models.