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Data Is Key Across the Sales Enablement Platform

Wow, My Business Is Doing Better Than Ever

My previous blog analyzed how technology and the right team can improve your sales enablement program. This blog explores the benefits that data can bring to your sales enablement program.

In addition to the technology and having the right teams involved, data – where and how it is sourced, stored, stewarded, refreshed, and enriched – is critical. Here are the key data-oriented success criteria considerations:

Data Acquisition/Sourcing

With the growing number of data sources and feeds about client contacts, sales and transactions – and market data from the company’s internal and external sources – the data acquisition life cycle needs to continuously be streamlined, standardized, consolidated, and monitored. Data extraction rules and data stewardship at the source are required before bringing data into the company’s sales enablement ecosystem. All this makes data acquisition management cost effective and facilitates good data governance.

Client Data Hub – Sales Intelligence

A client data hub is a critical data repository that houses all the data gathered from various sources and helps generate the “golden copy” record, which is derived with the help of pre-determined data rules that are overseen by data stewards. In addition, this data hub also includes a business rules engine where sales-specific rules (e.g., territory taxonomy tagging) and data distribution and summarization rules can be setup up for the benefit of downstream applications (e.g., CRM, sales advisor compensation, reporting).

Data-Driven Application Implementations

Applications, such as CRM, benefit from the client data hub because they receive the “golden copy” of data records that have been enriched. Unlike a few years ago when CRM solutions use to house and process a lot of raw data, try to make sense of it, and get it business-ready, CRM implementations are now data-driven with data ‘views’ that are relevant to application users.

In addition, CRM applications produce and maintain their own data (e.g., sales activity management data, new contact data) that can feed into the client data hub via a bi-directional interface. Similarly, other applications such as reporting, compensation, analytics, and predictive modeling benefit from ‘golden copy’ data that is stewarded upstream in the client data hub.

Greater Focus on Data With Artificial Intelligence in Sales

AI and machine learning are becoming key sales enablers for investment management sales teams. They offer intelligent forecasting, improved prospecting and campaigns, up-selling and cross-selling, price optimization, and sales performance management. AI’s many capabilities enable increased selling time and enhanced sales productivity.

For AI programs to continue to derive value from existing data and implemented applications, the ability to deal with the diverse (e.g., inaccurate data, high volume) nature of the data is important. Fortunately, AI itself leverages both structured and unstructured data and has the ability to assist in data cleansing.

AI/ML are set to gain momentum post-pandemic times when in-person sales contact decreases during the sales cycle. While the human touch in sales will never be replaced, it can be enhanced by technologies that allow sellers to concentrate on getting the right message to the right prospect at the right time. As data continues to fuel AI programs, focusing on getting the data “right” and managing it will become more critical than ever before.

Enterprise Data Lake (with sales and non-sales data flowing into it)

It’s common to have an enterprise data lake into which company and external data flows. In the case of sales enablement, the data lake not only sources sales data from the client data hub and various sales applications (e.g., CRM) but also non-sales data, such as investment product data, market data, and other client intelligence data that are outside of the sales group and company.

It’s crucial to leverage the data lake, as that’s where the data analysis team can marry sales and non-sales data to conduct detailed analyses on trending, surface new insights, identify gaps and revenue opportunities, and perform predictive modeling. As with applications, more value can be derived from data lakes with AI tools – and not just for sales teams, but the entire company.

Data Analysis

These days it’s hard to find a large company without a dedicated sales data analysis group that derives insights to determine revenue outcomes and set objectives for their sales team. Sales data can add value to non-sales teams in the company as well. As such, a data-driven sales organization can create value for marketing, customer support, product teams, and corporate strategy. Senior leadership needs to recognize this trove of untapped insights – and take steps to put sales data and analytics into action across the company.

Data Governance

Data flow is critical for sales enablement and all its tools, so it’s imperative to have a comprehensive data governance program to watch over sales-related data across all the essential components discussed in this guide: data sourcing, client data hub, downstream applications, enterprise data lake, and data analysis. Ideally, the sales enablement organization’s governance program should leverage, if available, enterprise-wide data governance tools as one of the many benefits will be for others in the company to have access to the sales metadata.

Timely, relevant, accurate, and governed data will strengthen the sales enablement organization and force other groups, such as marketing, to improve their data, processes, and support for the sales team. It may drive marketing automation and other transformative solutions and bring marketing and sales to work together more.

Sales enablement is a critical function that works in tandem with sales and marketing. Part of it is technology, and part of it is data. Data-driven strategies, programs, and tools for sales enablement are critical for investment management firms seeking to compete effectively, focus on the client, and win in a new operating environment.

To learn more about the role of sales enablement in investment management and the success criteria for an effective sales enablement program, download our newest guide.

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Nimish Puri

Nimish Puri is a senior project manager in the financial services practice with experience in leading teams to plan, analyze, implement, and manage strategic cross-discipline initiatives for technology enablement, process improvement, and business transformation. With domain expertise in investment management, wealth management, and data management, he works with clients to conduct strategic analysis and manage programs and projects.

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