Unfolding the Mystery of Sales Effectiveness; Seven Things Sales Executives Want but Can’t Get
Please visit http://insidebigdata.com/2016/03/26/unfolding-the-mystery-of-sales-effectiveness-seven-things-sales-executives-want-but-cant-get/ for the original article.
In this special guest feature, Ajay Khanna, Vice President of Product Marketing at Reltio, provides a data-centric view of the top seven things sales executives want but can’t get. Prior to joining Reltio he held senior positions at Veeva Systems, Oracle and other software companies including KANA, Progress and Amdocs. Ajay holds an MBA in marketing and finance from Santa Clara University.
Sales executive and sales operations teams are constantly challenged with acquiring and maintaining reliable customer data. Correct customer and account information means better understanding of customer needs, more sales opportunities and higher productivity. Even after substantial investments in tools and personnel, the problem of inadequate information persists. Sales executives need data-driven, personalized applications that help them with accurate planning and efficient execution. Such data-driven account management applications require a Modern Data Management foundation that bring data management, predictive analytics, graph and machine learning technologies together in a unified platform, with big data scalability.
Let’s take a look at seven things that sales want but struggle to achieve.
Accurate and complete customer information
Sales executives depend on complete and current customer information to manage their B2B accounts or individual consumers. More likely than not customer information is scattered across multiple systems (CRM, marketing automation, finance, support), marred with duplicate records, incomplete profiles, and incorrect information. The last thing a salesperson wants is to walk into customer’s office unaware of customer reported issues or promotions sent to them. Working with questionable customer data impacts the productivity of sales teams as well as the customer experience. As a result, sales stop relying on CRM and SFA systems and tend to create their own shadow processes and systems that work for them, leading to even more gaps in data reliability.
Every year sales operations spend a copious amount of time trying to get the sales alignment right. They are targeted with the most efficient utilization of sales resources to maximize revenue. But are sales operation professionals flying in the dark? They spend months gathering account, product, territory information from multiple systems, put in large spreadsheets, clean it up and then run the analysis. Disconnected data causes long planning cycles and confidence level in the plans is minimum. The sales strategy is based on questionable data. Moreover, data is continuously changing leaving the plans to be barely relevant when completed.
Understanding of the account hierarchies
Organization structures are complex. Sales executive’s responsibility is to understand that complex structure, the key stakeholders in the organization, their influence, and then tactfully navigate that maze to find and win an opportunity. No mean feat this is. The CRM and SFA systems do not provide them with this information. Third-party data subscriptions provide legal hierarchies of the account with linkages to individual business units. Such account information offers little help to sales to execute on the account strategy. They need a view of hierarchy that shows the relationships of key accounts and stakeholders that helps them understand buyer’s needs and move their sales cycle forward. The lack of hierarchy personalization without necessary rollups limits sales account understanding and plan execution.
In addition to an understanding of real-life hierarchies that help, sales executives also need to understand the relationships and influencers in the account. Information like who is the real decision maker and how is she organizationally linked to the other stakeholders, influencers, users, and budget owners is crucial. Finding the right person in a complex organization and developing champions who lead you to the finish line is a critical factor deciding win or loss. Traditional CRM, SFA or master data management (MDM) systems are not designed to capture and maintain information about relationships across customers, products, places. Sales executives have to learn this “soft skill” on the job.
Personalized view of information
Sales executives value information that uncovers cross-sell and up-sell opportunities and help move their deal forward. They want to know accounts that bought a product, which business unit in that account are not using the product, key contacts in the account where the product needs an upgrade and so on. They want the contextual view of all relationships that provides such insight. Current systems deliver one-size-fits-all information to all sales people across all territories and offerings, irrespective of the account strategy. Some needs are met by generating custom reports and unnatural contortions of existing systems, but disjointed systems and deficiencies in information prevent delivery of personalized view of sales data.
Leveraging and affecting marketing insights
Marketing collects information, like product and channel preferences from ongoing multichannel interactions with customers. Sales, and other customer-facing teams need access to this data. Armed with this information, field sales and contact center agents are able to have relevant and productive conversations with customers. On the flip side, the information that sales gathers in the field should become input into marketing activities. The feedback from the field can include a customer address change, suggestion for a content piece, or request for a channel subscription. A closed-loop coordination is essential for maintaining meaningful engagement with customers. Departmental silos, and lack of processes to share and collaborate across teams make this impossible.
Some salespersons are better than the others with understanding customers' needs. They are diligent about gathering customer information from all available sources and proactively fine-tuning their account plans. The challenge for sales leaders is first, to find such sales superstars and secondly, to design sales processes for consistent delivery. In the absence of predictive analytics and machine learning capabilities, sales remains more of an art than science. Sales organizations need systems that monitor customer interactions, understand customer profiles and preferences, uncover new relationships and recommend next-best-actions for sales executives. With such guided recommendations, salespeople can execute on plans more efficiently. With guided recommendations, all account executives can become your best account executives.
Enter the age of data-driven applications
Data-driven applications for customer and account management are built on a Modern Data Management platform that blends data from all internal (CRM, Marketing Automation, ERP), external and third-party data sources to create a foundation of reliable data. With capabilities like matching, merging, de-duping and address verification, data is always kept accurate and complete. High-quality customer information means informed account plans, proper sales alignment and better customer engagement.
Data-driven applications leverage a columnar and graph hybrid store to manage information at big data scale, and uncover relationships among accounts, contacts, products and places. Unlike off-the-shelf pure graph databases, a hybrid store is infinitely scalable, handling MDM and big data volumes with ease. Now sales executives can discover and leverage relationships to reach out to influencers or find product gaps in the account hierarchy. Graph technology allows them to pivot information from account, contact or product perspective in an instant. Industry and role-specific applications can be created on a unified reliable data foundation to provide more personalized and contextual customer information, without a need for data duplication across systems.
When the reliable data is combined with predictive analytics and machine learning, relevant insights can be delivered. The system can suggest new relationships or next-best-actions to all customer-facing teams, and helps design actionable account strategies. Sales can now uncover new relationships in account networks, and understand the influence of these relationships impacting their deals. Contextual and role-specific data-driven applications with graph technology take sales execution to a whole new level with unprecedented account and customer understanding.