Today, revenue growth is about retaining the customers you have and exercising rigorous efficiency in how you generate new business. To thrive, the customer experience must be cohesively designed from prospecting through renewal. Optimizing the entire revenue lifecycle means applying one strategy across sales, marketing, customer success, and product teams.
When a customer buys your product, it doesn’t matter to them that sales and marketing are two teams. It only matters that they have a great experience at every touchpoint as they consider the purchase, decide to make it, onboard, and eventually renew or expand. An optimized revenue lifecycle considers the entire customer experience, increasing net revenue retention by improving that experience.
Three Necessary Changes
The optimized revenue lifecycle necessitates a shift that includes the creation of a new leadership role, the lengthening of strategic timelines, and the implementation of data-led intelligent automation.
Create a new C-level role – In an optimized organization, all revenue including new business, expansion, and renewal is owned by one C-level leader that works toward one shared strategy built around the customer. Roles are specialized as they are today, but vision and goals are shared.
Create a 3- to 5-year strategy – Customer relationships last indefinitely, so an optimized revenue organization needs to plan 3-5 years into the future, anticipating what customers will need tomorrow while executing on what they need today.
Invest in Intelligent Revenue Automation – To drive the most efficient and effective revenue growth and protection possible, optimized orgs combine their system of intelligence with their system of action. This shared Intelligent Revenue Automation system ingests information about every customer touchpoint, delivers insights, and automates workflows that free people to focus on the activities that directly drive revenue.
Optimization from Prospecting Through Renewal
To create a cohesive customer experience, the revenue organization must share information. An optimized revenue lifecycle starts with connected data across your sales, marketing, and customer success teams, and includes in-product activity. Start with your CRM, MAP, and product usage data, plus any third-party data you want to use.
Connecting your data unlocks your team to gain efficiencies throughout the entire funnel. It’s the first step beyond human scale account prioritization, activity tracking, performance scoring, speed to outreach, forecasting, and risk reduction. At least 30% of manual work on revenue teams can be eliminated through optimizations such as these four workflows.
Identify Your Best Prospects
Flag key metrics to prioritize contacts and accounts in your pipeline. Automate the digging to find contacts who take valuable actions (for example, coming to a webinar and then looking at multiple site pages). When your BDR team starts the day with a list of these prospects, they spend more time doing what they do best rather than generating hit-or-miss prospect lists.
Use AI to Monitor Daily Activities
Move out of spreadsheets into a data-led system with a daily pipeline forecast and easy deep-dive metrics for every person on the team. Analyze historical deal data to set the right activity targets per deal type and rep level. Validate that the team is engaging with ideal accounts and reaching out to the right number of contacts. Send an automatic, personalized email to a customer as soon as they signal expansion readiness.
Forecast for Course Correction
Gone are the days of relying on rep calls to forecast where your quarter will land. An optimized team forecasts at least 12 months out based on automated analysis of deal indicators that reveal whether accounts are moving at the right pace to close as expected. The longer time horizon allows for streamlined course correction while deals can be saved.
Flag Revenue Risk at the First Signal
Spotting revenue risk within a cohesive journey starts by analyzing lost and renewed customers over the past six months. Then, identify actions that are prevalent and frequent among each set, but not in both sets. If lost customers and renewed customers both logged in every Monday, knowing that someone logged on Monday isn’t meaningful. If only lost customers logged in fewer than three days per week, you know to flag low logins.
Getting Back Valuable Time
While much of optimization through the revenue lifecycle comes down to intelligent automation, the value lies in freeing people to do revenue-driving work that only humans can do. As much as I advocate for Intelligent Revenue Automation, I encourage revenue leaders to protect this “found” time for their teams to do creative work, strategize, and learn directly from customers. Optimization is about a holistic approach, not only more efficient operations.
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