Get the data right first, then build your distribution strategy and infrastructure around it. That was the key theme from a panel I moderated at The SME Forum last month. The topic was inspired by Ignites’ article Data Bytes: Sales Teams Struggle to Use Analytics and panelists shared insights into their progress and some obstacles they have encountered in the pursuit of a data-driven distribution strategy. After having some time to reflect on their insights, here are three approaches asset managers are using to get the data right and use it effectively in distribution.
Streamline and sequence your approach
Establish a data strategy and infrastructure that will bring your first-party marketing and sales activity data together with your third-party data into a single system of record. This will ensure you have a central repository for your analytics and when integrated with your CRM, one place for your sales team to work from so they can easily access the data they need.
Consider the pros and cons of buying versus building technology to support your strategy. Buying technology involves working with a partner to configure the system. Building has proven to take more time and be a bigger drain on internal resources to maintain.
Get your data right, first. This will inform how your CRM should be configured to position the data at the fingertips of your sales and marketing teams. One of the biggest lessons learned by our panelists is how crucial it is to understand how the data is going to be flowing into the CRM. Building out the CRM in tandem with, or prior to, the data management hub presents complications and as a result, the data may not match up. Work on the data structure first and then build tools around it.
Determine “good enough” data cleanliness
While writing Data Bytes, panelist Carmen Germain found that asset managers have taken steps to incorporate data analysis in distribution and have buy-in from leadership, but few [only 80% of the 10 asset managers surveyed by ZS Associates] saw small improvements. The main reasons:
- ROI is difficult to measure. From a September 2019 Ignites article, only 24% of firms were trying to calculate ROI.
- Different departments (sales and marketing) have different objectives and sometimes data and analytics efforts are duplicated.
- It is time-consuming and sometimes nearly impossible to get the data perfect.
If you’re struggling with measuring ROI, start by measuring usage. What analytics and data are your people using? Who is using the data and how often? Why do they use it? Talk to the users of the data and ask questions about how it has helped build relationships and grow sales. Look at it from the standpoint of the users of your data to understand the value you’re getting out of it.
The saying “Perfect is the enemy of good” is never truer when it comes to data quality. Decide what’s “good enough” and measure impact in a way that makes sense for your organization. Have a goal (the data doesn’t have to be perfect) and build a consistent process.
Incorporate data analytics into your culture
Bake data analytics into the sales team by providing a CRM with a good backbone, or distribution data platform with clean data coming in and going out. Create customized dashboards and reports for the individual to allow them to work the way they need. By making the data accessible through the CRM, sales teams can self-serve to hone their efforts.
With a marketing-first approach, or as one panelist referred to it “a digital twin to personal sales”, marketing takes the lead on engagement. Much of the activity in your buyer’s journey is marketing-driven and complimented by personal, human engagement from the sales team at crucial stages like the point of sale or for retention. Investing in data and building out technology and resources within marketing and analytics teams will make this journey much smoother. Their objective will be prioritizing data collection (avoiding interrogation) and expanding the breadth of the data model.
Where do you start?
Whether you’re starting from scratch, due for an overhaul, or fine-tuning, be sure to establish a data model and get the right people involved in the governance of the data. The data model will be the base for everything—from expanding marketing to building a data science team and using AI tools. No matter what it is, a solid data model will allow you to do analytics at any level and strengthen your sales and marketing teams.
If you’d like to talk about what approaches may be best for your firm, contact us. We only work with asset management firms and can help you to assess approaches and solutions that will work for your unique circumstances.