The Indian SaaS ecosystem is experiencing longer software sales cycles in 2023, despite an overall bullish outlook. This is posing a challenge to the sector’s growth, as 51% of CXOs acknowledged in a recent industry report. To manage this challenge, it is crucial to prioritise high-quality leads, aim for quick deal closure, and focus on sustainable growth.
At SaaS Labs, we have made automated sales forecasting a business imperative for efficient growth and revenue enhancement. We rely on automation and AI to arrive at precise sales forecasts, and use Salesforce Forecasting and Pipeline Management Software to achieve this.
Why is automated sales forecasting important?
Apart from delayed customer closure cycles, the Indian SaaS industry is also witnessing uncertainty in terms of valuations and capital inflow. Hence, it is essential to prioritise short-term revenue predictability to achieve immediate business goals. This marks a significant shift from the traditional focus on long-term client commitments and perceived account value. The focus today is on actual, immediate product consumption.
Automation is key to achieving accurate sales forecasting, and driving increased accountability and ownership within sales organisations. Unlike traditional spreadsheets that rely on static data viewed over time, a CRM solution allows businesses to automate and streamline processes, capture and consolidate data, and race through that data in real time. This creates opportunities for intervention and ensures that relevant team members are promptly alerted to any delays or issues in the sales cycle.
With automation, pipeline and forecasting management become more effective, even when handling large and complex data sets. Businesses can easily monitor and manage every aspect of their sales pipeline, ensuring that they prioritise the highest quality leads and work towards quick deal closures. Ultimately, automated sales forecasting provides businesses with the data and insights they need to drive sustainable growth and achieve their revenue goals.
How SaaS companies can use automation in sales forecasting for efficient growth
Define the sales cycle for each product
Each software offering typically has a different sales cycle involving a unique set of touchpoints. That’s why it’s important to define the stages of a software’s sales cycle clearly and integrate these into your sales process. Depending on product complexity and an analysis of customer data, you can determine the average time it takes for a lead to convert and the number of demos needed per account. Automating the process of mapping out these unique touchpoints makes it easier for you to track progress and optimise the sales cycle for better results.
At SaaS Labs, this process has given us insights into why a deal is entering a particular stage and what are the entry and exit criteria for those stages. Having a defined process lets us review if a particular deal is progressing in the right direction and facilitates high level as well as granular level visibility.
Create an advanced software revenue forecast model
In a highly uncertain business environment, it is essential to rely on data rather than guesswork and intuition while creating forecast models. Traditional spreadsheet-based models aren’t exactly accurate when it comes to sales and revenue forecasting. An automated forecasting solution built specifically for the SaaS ecosystem helps leverage ML algorithms that factor in historical demands, trends, and ongoing engagement opportunities. This data helps create a predictive model that greatly lowers the risk of gaps between sales forecasts and actual revenue.
Quick access to centralised data – that includes everything from log in activities to meeting bookings – is vital today. Integrate data from multiple sources into one central repository to create a single source of truth. This can help you streamline data management, improve data accuracy and provide real-time visibility into key business metrics. Including identifying factors that contribute to successful deals; for example, activities performed regularly by sales reps, such as calling or sending emails, that increase the probability of deal closure.
At SaaS Labs, we use data consolidated on Salesforce to upsell, boost ticket size purchases, manage churn, and access real-time visibility into revenue predictions.
Identify trends and patterns from historical pipeline data
It is important to analyse historical pipeline data, both in terms of numbers and the quality. Automation can help analyse complex pipelines quickly, identifying patterns data around the company, customer behaviour, prospects and opportunities, and so on. Intelligent automation, leveraging ML algorithms, also helps monitor market conditions and industry trends. Automation also offers the power of predictive analytics, which aid account territory planning and influence other aspects of strategy.
Create forecasts at all levels
Forecasts at the company level help inform strategic planning while at the department or team level, it can aid operational planning. In this context, automation is a valuable tool; SaaS companies can leverage automated solutions, workflows or custom APIs for data collection and integration, create statistical models that can automatically generate forecasts, or create dashboards and reports that provide real-time insights – all at scale.
By automating forecasting at all levels of organisational hierarchy, SaaS companies can reduce manual effort and errors, and ensure that the data is accurate and up-to-date. Multiple layers of forecasting can ensure that teams are operating efficiently, monitoring areas where improvement is needed, and improving collaboration.
Driving comprehensive sales forecasting with an intelligent, automated solutions
As a sales and revenue ops leader in the SaaS ecosystem, SaaS Labs realises the importance of driving greater short-term revenue and sustainable growth. You can replicate our approach by investing in industry-specific forecasting tools that help integrate historical demand, engagement on an opportunity and revenue predictability to grow your SaaS business.
An ideal solution should facilitate comprehensive and scalable forecasting powered by automation and predictive AI. It should allow you to drive predictable revenue and track progress in real time by providing:
- Comprehensive views of your business and pipeline
- Real-time sales forecast visibility for timely adjustments
- Actionable data insights and predictive AI for high revenue impact decisions
- Intelligent pipeline management and AI-led support for priority deal closures
With the help of Salesforce’s Sales Forecasting and Pipeline Management Software, you too can build flexible forecasts that cater to the needs of an agile business environment and unique business models.