Catchlight populates profiles on leads and contacts with hard-to-find data like estimated or predicted:

• Investable assets
• Income range
• Age range
• Personal and financial interests
• Life events
• Home value
• Career details and more
  

For illustrative purposes only. New client conversions using Catchlight lead prioritization assumes higher call rates focused on prospects with greater chances of converting and variable conversion rates for low, medium and high chance leads. Potential additional conversions assumes higher chances of conversions by incorporating more personalized engagements using Catchlight insights.

Here are some hypothetical results Emily's firm might achieve using the Catchlight Score:

Let’s assume that half of the 50,000 leads generated by the marketing team are being pursued by BDRs, or 25,000 leads. The average AUM per qualified lead is $1 million. Most leads are form fills providing basic info like the prospect’s name, email address, phone number and in some cases self-reported financials.

Emily is currently sending these leads to BDRs using her simple lead scoring system. As a result, BDRs are splitting their efforts equally across all leads, which are categorized as follows: high (30%), medium (50%) and low (20%) chance of conversion to clients.

Using the Catchlight Score, BDRs can focus most of their attention and resources on prospects with the highest chance of converting. For example, by focusing a majority of the calls on the high-chance leads and allocating only a small amount of time to the low-chance leads, the firm could potentially close more clients per year, resulting in additional AUM per year.

All things being equal, even a slight 0.1% uptick in conversion rates could have a significant impact. And the firm could welcome even more clients if its conversion rate increases another 0.1% through personalization powered by Catchlight insights.