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Case Study
Distribution data platform drives US retail sales growth
Client Challenges
A $650bn AUM US asset manager faced fragmented, low-quality data across its client group, blocking meaningful insight into client and prospect behavior. Disconnected systems created inefficiency and risk across marketing and sales functions, undermining growth potential in the US retail channel.
alpha approach
Alpha facilitated a compelling vision for change before designing and co-developing an integrated sales intelligence platform for the US retail business The solution combined a ML-driven data processing and quality control engine with a unified CRM and BI ecosystem delivered through a single UX built in Python on AWS. Salesforce was upgraded with productivity features including a client preference center broker fund availability data and RFP integrations External sources such as SS&C Salesconnect Walletshare Morningstar and Envestnet were combined with internal signals from Marketo Adobe Seismic and LinkedIn to generate buyer intent models The platform transformed the client’s US retail sales capability enabling data-driven prescriptive coverage across RIA and BD channels at scale
How we delivered lasting value
Turning insight into impact
Prescriptive Sales Insight Surfaces Probable Buyer Opportunities
ML-driven intent signals and digital engagement models put actionable opportunities directly in front of salespeople, replacing manual prospecting.
Clean consistent data eliminates inefficiency and risk
A centralized quality control engine delivered reliable, unified data across sales teams, reducing operational risk and improving daily workflow.
Integrated CRM ecosystem maximizes platform ROI
A single UX connecting Salesforce, BI tools, and ten internal and external data sources increased productivity and returned measurable value from existing technology investment.
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