J.P. Morgan Asset Management, one of the world's premier investment organizations and manages over $2.0 trillion in AUM. We are committed to being the investment manager of choice for our clients and providing critical insights to help clients make informed investing decisions.
We are looking for a multi-talented, analytical leader with strong commercial instincts and a desire to shape business strategy and outcomes.
The successful candidate will be part of JPMAM’s Business Intelligence team, a team of 8-10 multi-disciplinary data scientists and strategists from various backgrounds. The mission of the team is to use data to optimize our distribution (sales team) and marketing efforts/investments to increase JPMAM’s market share.
We figure out:
Where future growth will come from and how to produce sales alpha
What new initiatives/strategies best increase market share (and which don’t)
How we need to reshape our operating model and re-allocate our resources
Some past, current and future strategies include:
Creating an end-to-end client segmentation framework that uses innovative machine learning techniques to stitch external and internal data together
Launching our ETF distribution strategy (which clients to prioritize and what products to sell them)
Building a product recommendation engine for all client segments
The Business Challenge:
JPMAM is a B2B environment. Unlike many consumer retail businesses, there is no “closed-loop”. We know what our client engagement is (either through web, email and in-person meetings) but our clients’ “purchases” happen off-line on their respective platforms. Thus, sales attribution and ROI calculation becomes a science in uncertainty.
Client data in the asset management intermediary business is not standardized. Our sales can come in large ‘blocks’ that are rolled up at the firm level or they can come in at a granular, client level. Advisory purchases are not always differentiated from brokerage purchases in the same way across firms.
The distribution organization has historically been ‘sales-led’, with marketing and digital efforts taking on a sales-support and sales-enablement function. However, the client landscape is evolving with client preference for engagement moving towards digital mediums.
This is a challenging role. The data is not perfect nor is it complete. The marketing organization finds itself in a transitionary period moving way from sales-enablement to directly activating prospects and deepening existing clients. We have made significant progress in creating a centralized data lake with a single view of the client…but still have a long way to go to integrate marketing data. KPIs are not always consistent, definitions change.
For the right person, this challenge is energizing. This is a call for leadership, prioritization and data-driven decision making. It is equal parts analytics as it is transformation management. All the right components are there: world class products, the best distribution team and industry leading client engagement platforms. We need someone who brings it all together to help inform and execute an unbeatable marketing strategy.
The Successful Partner:
The success of the role is largely dependent on the successful partnerships the Head of Marketing Analytics forms with key internal stakeholders. Some of these are:
Segment Marketing Team: Partner with the segment marketing team to perform campaign analytics, recommend marketing/digital only micro-segments (within the larger segmentation framework). Partner with the team to articulate a segment marketing strategy and how data can be used to create maximum business impact through activation or deepening.
CRM/Operations/Technology: Inform and own the marketing data architecture and data stack. Own marketing data governance and data lineage (What is golden source? Where is the missing data?). Articulate self-service/dashboard strategy.
Digital and Brand: Work with the brand and digital teams to optimize our programmatic spend and ad buys. Provide both teams with an analytical framework and KPIs for the digital analytics team to optimize performance, digital experience and tactical campaigns. Work with Head of Martech to roadmap future state analytical capabilities, including but not limited to DMP.
The successful candidate will also be a self-starter, introducing and socializing concepts that the larger enterprise has not yet formalized, including:
What does marketing data governance look like?
What should the Marketing Analytics engagement model look like? Today, it is largely reactive and ‘most urgent first’.
What is our prioritization framework? What is our ‘success’ yardstick?