A recent study revealed that 38% of companies still lack a customer success tool. Without proper technology in place, post-sale teams often resort to old-fashioned spreadsheets and email threads to determine how to service and engage customers.
But manual, disparate systems put customer experience teams at a disadvantage. With siloed information, they may miss vital data to inform:
- What content to send customers and when.
- Team training to meet customer expectations and improve customer experiences.
In the absence of data and actionable insights, missed opportunities stack up. Fortunately, customer success professionals can leverage technology enhanced with machine learning (ML) to improve customer retention, growth, and success.
Collaboration drives customer retention and business growth
Many companies still conduct sales operations in silos, where a seller closes a deal and immediately passes the account to an implementation or customer success team for onboarding and management. The handoff is often the first time a customer interacts with the post-sale team. In this case, post-sale teams rarely have prior knowledge of the account and instead rely on often incomplete information logged in a CRM. Unfortunately, a lack of information can cause mistrust from the start.
Today’s post-sales teams have a massive opportunity to streamline internal workflows and enhance the customer experience with the same revenue enablement tools used by sales and marketing. Standardizing processes across all go-to-market teams allows you to reduce the overall time to launch and ensure everyone receives the same level of service across the customer journey. Companies can dramatically increase internal and external efficiencies by creating a seamless transition from pre to post-sale.
Improve engagement with a value selling approach
Value selling is a customer engagement strategy that helps commercial teams shift conversations from features, delivery, and adoption of products and services to expected value outcomes throughout the customer lifecycle.
Post-sale teams that adopt a value selling approach have more meaningful quarterly executive business reviews (EBRs) focused less on operational objectives and metrics and more on usage, business value, and ROI. They also see more renewals and up-and-cross-sell opportunities.
Customer success teams can take the following steps to begin value selling:
Align with customers on critical business objectives – View solution delivery from the customer perspective, and understand how it will help them meet critical business objectives.
Identify the right metrics to track – Document key performance indicators (KPIs) — cost, productivity and processes, business risk, and growth — positively impacted by the solution.
Tally historical benchmarks – After identifying key metrics, record the KPIs’ starting values before implementing the solution and improvement.
Quantify improvements – Measure improvements and communicate those to the customer. Do this via stakeholder surveys, discovery questions, reports, or a solution API.
Use KPI impacts to quantify business value – Move beyond a typical list of KPI impacts. For example, convert improvements into financial business benefits, savings, or growth.
Determine ROI and net economic impacts – After documenting value, compare gains and savings achieved versus the investment. Collect licensing and infrastructure costs for the solution or service, expenses for customization, services, deployment, project and change management, and training.
Humans and machines working together
Communicating realized value is essential to retaining and growing existing customer accounts. Post-sale teams must deploy several key capability/maturity improvements across five areas and continue evolving them as they deliver and scale the program.
People – Elevate skills within the post-sale team to ensure everyone can engage customers on realized ROI. Empower and coach team members to transition discussions from implementation, project management, triage, and adoption/usage to business objectives, KPIs, and business value.
Process – Use customer success platforms to manage and host impactful Quarterly Business Reviews (QBRs) focused on realized value.
Tools – Leverage value selling tools across the customer journey, including a Realized ROI calculator post-sale, to consistently earn clients’ business and drive renewals.
Integrations – Integrate all commercial applications and tools with the platform where sales and post-sale professionals live and breathe (e.g., Gainsight).
Intelligence – Unify data from value assessment tools, sales activity capture solutions, and content engagement platforms in your customer success platform for a 360-degree view of objectives, challenges, intent, historical information, and ROI. Use the insights to identify risk, inform customer engagement, and accurately forecast growth opportunities.
Customer experience and account growth benefit from a symbiotic human-machine relationship. Post-sale teams leveraging ML-empowered technology can identify the customers most likely to guide customer success engagement focus and triage.
It costs businesses five times more to close a new account than keep an existing one. Thus, companies are increasingly holding customer success professionals accountable for revenue. It has become critical to empower customer success and growth teams with the same content, technology, and resources traditionally supplied to sales professionals.
Together, humans and machines enhance the post-sale experience, increasing customer satisfaction, retention, up, and cross-sell opportunities to drive business growth.
