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RevOps aims to maximise an organisation's revenue, but the strategy can face an uphill battle. Artificial intelligence (AI) can overcome some of the challenges of RevOps and add to the strategy's strengths to augment a company’s desired revenue inflows.
Revenue Operations (RevOps) aligns sales, marketing, and customer operations to drive growth through efficiency and focus all departments, people, and platforms as one entity toward revenue growth.
RevOps can streamline internal processes, augment client conversions, increase customer service, and remove departmental siloes to create a revenue growth-focused culture.
Several constraints are typical when following a RevOps route; we’ll look at those before discovering how AI can empower a RevOps strategy.
Organisations have historically grown into siloed departments with their own goals and with problems solved disparately with each team.
As companies, markets, and customers have grown, so too has the realisation that teams, people, and processes must all work together for efficiency, competitive advantage, and revenue generation. Customer and marketing technology has become increasingly important.
Data is one of the most influential business assets today. Clear, accurate, real-time insights drive fast, impactful decision-making that quickly positions any business ahead of its peers.
Today’s problem for businesses, especially those behind in digital transformation, is the sheer number of data touch points and channels and then how to collate data and analyse it appropriately for powerful insights.
If the problem of reams of fragmented data and data sources can be solved, the insights garnered to serve complex market needs and customer expectations are invaluable.
It’s no longer feasible to rely on past trends, last year’s market data, past experiences, and gut feelings. If a competitor has real-time insights and you don’t, they are miles ahead.
Not only is data disparate and disconnected, but so are departments. RevOps's goal is to bring departments, people, and processes together for revenue growth, but that’s a difficult task in established teams, extensive markets, and whilst serving customers.
Siloed departments have disparate KPIs, and overall goals are often the responsibility of a team leader and rarely analysed side-by-side across development, marketing, sales, and customer service despite every team working for the customer.
Siloed departments, disparity, and management hierarchies without cross-functional impetus struggle to understand the purpose of RevOps and sometimes even of revenue generation.
Revenue goal sharing as a company culture is vital, but, as examples, often marketing departments don’t feel responsible for converting customers, and production-focused teams have an insular goal of volume output, problems solved, or projects completed.
A RevOps strategy may incorporate a RevOps machine, advanced CRM, engagement platform, or productivity platform.
Or, a RevOps-aligned tech stack may consist of several platforms and applications that work seamlessly together for a business's unique needs.
AI’s integration, either passively by its inclusion in platforms from existing suppliers or intentionally by the company choosing AI-powered applications, can have numerous benefits for a RevOps strategy.
AI can analyse data and workflows to highlight areas for improvement, knowledge gaps, and areas of low performance. AI can also automate tasks and streamline workflows, picking up labour-intensive and monotonous tasks and freeing human employees to focus on more motivating responsibilities, problem-solving, and creativity for further innovation and product iteration.
AI’s benefits are dual-fold here too. An AI or ML-powered platform can quickly get to grips with multiple data sources, data perimeters, and thousands or more data items. It can collate this data, analyse it, and create a flow of real-time enhanced insights not just at the fingertips of business leaders but also for every department and employee.
AI-powered planning and forecasting solutions can process vast amounts of historical data, trends, and customer behaviours and expectations to coherently power planning and forecasting. Leaders can visualise a sales pipeline with a few clicks, for example, without the sales team spending hours manually recording their activities.
Today’s nascent AI technologies, when risks are mitigated, are transforming sales processes internally and externally and rapidly advancing the customer experience. AI-powered tools can analyse customer interactions, sales calls, and meetings, perform sentiment analysis, and identify conversion opportunities.
AI can process reams of prospect data, including past purchase history, identify quality leads, perform lead scoring, and give actionable hot lead lists to sales teams. It can also answer basic inquiries, leaving human teams to answer complex issues and make conversions.
Customer satisfaction is vital to revenue growth, and AI enables faster, personalised, and efficient customer support in multiple languages and at any time.
The right AI, automation, and platform choices can do the initial work of a RevOps team, collating data and connecting departments so human leaders can focus on robust KPI and goal setting and creating a culture of RevOps throughout departments and corporate hierarchies.
Newly revenue-focused teams can work side-by-side with technology and AI tools faster and more efficiently with compelling data to drive revenue through excellent customer service, targeted sales, and potent marketing.
AI can solve the key challenges in a RevOps strategy, conquering data, fuelling customer and market understanding, and connecting goals, metrics, and the repository of knowledge every employee needs. RevOps leaders and revenue-generating teams have time to understand, share, and implement a successful strategy for revenue growth.
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