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The only agenda for high-growth enterprises today is a superlative customer experience. At forward-looking organizations, customer focus is at the heart of any digital transformation initiative. The technology must be agile and intelligent to ensure a positive customer experience from day one. And if you think you have time to smooth out your customer satisfaction checkpoints, think again. Retail customers have indicated time and again that they are willing to walk away from brands after one bad experience.
As enterprises revisit their tech stack to take their customer experience to the next level, customer relationship management (CRM) is the ubiquitous starting point, as it is a vast river from which millions of streams of information flow. So, how do we draw the paths that connect these streams to form data streams that help sales teams navigate directly to desired customer outcomes?
CRM: a registration system
To deeply engage with customers and their preferences, we need CRM data to dive deep into a customer story and provide clues to complete it. As we study demanding customer profiles, it is clear that sales teams can no longer build a formula based on this available data. Every job is now more complex and requires personalization and management.
Just having multiple data points is no longer enough. While modern CRMs are great for managing customer profiles and pipeline forecasting, we need AI-driven engagement systems that provide a sales team with not just the “what” and “when” but also the “how”, “who”, “how not” to’, ‘If’ and ‘Instead’.
Let’s look at some aspects where CRMs fall short in the context of modern sales and distribution.
- Politeness: While trying to understand how consumer buying behavior is constantly changing with the economic landscape, CRMs fail to capture which sales behavior and engagement are most effective – and which customer demographics. There are no sales playbooks that outline these tectonic shifts in buying behavior.
- ease of communication: As powerful brand as BlackBerry once was, the company can thank a failed CRM implementation for some of its spectacular demise. Instead of reaching customers through their preferred medium as the flagship messaging service collapsed, it used Facebook (now Meta) as its communication channel.
Omnichannel engagement is the way forward and organizations need to dig deeper into customer digital behavior. Can a system understand whether a consumer is digital by need or digital by choice? Or can it understand which actions a customer prefers to take online versus which actions they prefer to take through live engagement?
- Seller knowledge and expertise: Sales teams have a high turnover rate. According to HubSpot, at a hefty 35%, it is almost three times higher than that of other industries. This translates into a high rate of knowledge loss and best actions every time a salesperson leaves a team.
In 2001 British Airways implemented its Customer Data Warehouse (CDW), codenamed “Ocean Wave”. It took more than two years for the analytics teams to use the information for campaigns and reporting, primarily due to the complexity, time, and effort required for contractors to train system users on how to access and use the data.
To avoid a similar situation and lengthy implementation delays, sales teams need a system that captures best practices as lessons and transfers them to newer team members to enable:
- A fast onboarding process and shared access to the established knowledge pool;
- Seamless customer journeys.
- Transparency and ease of process: Most CRM users update their systems erratically, resulting in inaccurate, incomplete, or unreliable data. To create a seamless experience and transparency for customers, a CRM must include complete visibility into customer information, playbooks that suggest the next best actions, drive sales teams to take the right next steps, and complete visibility into team activities for sales team managers. But how often are CRM systems updated immediately after a sales order?
The need: a system of insight
A mobile and intelligent layer on top of a CRM system can convert a passive registration system into a contextual insight system. Real-time data, artificial intelligence, and machine learning capabilities help turn a CRM into a recommendation system that helps sales teams close more cases faster and improve the overall customer experience. The following features — in addition to robust CRM data — can improve engagement and customer experience by leaps and bounds:
- Automatic activity capture: A feature like auto-capture removes the biggest barrier to a CRM: manually entering data. Capturing in-depth data can be simplified through features such as automatic call and meeting detection, one-touch call sentiment, and note-taking.
- Identification and Emulation of Winning Behavior: If intelligent platforms can identify winning behaviors based on this extensive data collection, the identified behaviors can then float to the surface as nudges for teams to emulate. For example, suggesting an ideal number of touchpoints, tiering and prioritization, as well as personalization.
- nudges: Once the system can identify winning behaviors, it should be able to use these lessons to drive teams as they sell and interact with customers. This gives sales teams very specific guidance through different phases of engagement with a prospect or lead. Examples are:
- When is the best time for a second interview?
- Customer A’s service request has been resolved by the service team, start the following steps.
- Customer B’s renewal is in 30 days. Start the extension.
- Tina from your team has a meeting with platinum customer C in an hour. Would you like to schedule a coaching conversation?
- Customer D is similar to Customer B and this pricing strategy worked best for them before…
- New lead M is a mile away from your next meeting. Want to schedule an appointment on the go?
The possibilities! If the terabytes of CRM data can be mined into such nuggets of information for sales and customer service teams, it really empowers them and paves the way for outstanding performance and a superior customer experience.
Venkat Malladi is co-founder and CTO of Vymo.
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