Wilson Allen

Innovation Forum: Watch again

During each monthly session we will discuss a whole new world of opportunities that exist in your data. Register, join us live and bookmark this page to watch the recordings. If you have suggestions for future topics send your questions to data@wilsonallen.com.

Innovation Forum: The Client Churn Challenge

Client churn is a source of concern for many firms. During this community forum we discussed strategies for client retention and technology that you can use to develop insights. Topics covered include:

  • Using Machine Learning to analyze client churn data
  • Features that can drive client retention and which put a client at risk
  • Wilson Data Cloud, Azure Synapse, and how to use Big Data tools to ML at scale

This session will interest Marketers, Finance, or Business Development professionals looking to solve for client churn, or Data Scientists or Analysts who would like to discuss client retention strategies.


Innovation Forum: ROI on Marketing and BD Efforts

During this discussion, we explored the ability to thread together marketing and business development’s activities with relationship data to find which efforts drive new business. Using existing sources like the CRM, PMS, and campaign systems, we add relationship data to the mix to get even greater clarity on ROI. Data is power! View this session to take away example outcomes that can convince the most sceptical of principals and attorneys the value of tracking opportunities to marketing and business development.


Innovation Forum: Client Segmentation on Financials

Whether your firm has started investing in bringing your data sources together or not, disparate data is a pain point for most. And the reality is, making data-driven decisions to drive growth, improve client relationships and increase revenue is the way of the future. But how do we bring all this data together to get there?

In this session, Client Segmentation on Financials, we shared our model on how to value clients using recency, frequency, and monetary data points.

With Greg Murphy, VP Innovation

Watch Now! Wrong-Fit client segmentation

Watch this video – Liz describes how to leverage a data lake to combine previously siloed data from disparate systems, and build a holistic definition of (in this example) client health from a broad range of features.

Liz built this model to establish metrics to identify & segment clients by client health – bringing together data from financials systems (3E), sentiment scores (Clearlyrated), relationship strength (Introhive), and opportunities data (Salesforce). The algorithm groups the data points, each representing a client, into segments sharing similarities across the feature set. Through machine learning and data science, Liz has broken down a problem that wouldn’t be possible for a human to complete – taking 500, 1000, 2000 clients, and within seconds categorizing them into actionable client segments. Then you can drill down into the ‘wrong-fit’ segment – prompting decisions and actions that may then be appropriate – whether to funnel resources away from them into an ‘opportunity’ client segment or use this as an intervention opportunity for clients at risk – you’re now making these decisions backed by DATA.

With Liz McLaughlin, Data Science Associate