We’ve all heard the saying:
“Half the money I spend on sales and marketing is wasted. The problem is, I just don’t know which half.”
In today’s data-rich world, that uncertainty no longer needs to exist. Businesses are using one of their most valuable tools — data science— to cut through the noise and make confident, informed decisions.
When used effectively, data science to increase sales gives organisations a powerful competitive edge by enabling more targeted, efficient, and agile sales strategies.
Why Use Data Science to Increase Sales?
In a fast-moving marketplace, success depends on being proactive, not reactive. Data science enables this by transforming data into insight — insight that fuels smarter decision-making across sales planning, resource deployment, and customer engagement.
Using data science to increase sales helps businesses to:
Our Liquid approach to Sales Strategy
At CPM, we use strategic planning to uncover our client’s biggest sales and customer experience opportunities and apply data analytics and technology to ensure we have the right resource, in the right place, at the right time — this is what we call our Liquid approach.
This agile, insight-led model enables us to flex and scale sales activity based on real-time performance data and shifting customer behaviours. By combining human expertise with precise analytics, we help our clients maximise every opportunity — whether it’s launching a product, entering a new market, or boosting conversion in-store or online.
The Four Key Types of Data Analytics Driving Sales
To get the most out of data analytics to increase sales, we guide our clients through four essential levels of insight:
Descriptive Analytics: What Happened?
Descriptive analytics focuses on past performance. It turns raw data into dashboards, charts, and KPIs that show what has already occurred, helping clients understand trends, seasonality, and sales behaviours.
Diagnostic Analytics: Why Did It Happen?
Once you know what happened, the next step is understanding why. This stage helps uncover the causes behind sales patterns, such as promotional impact, store performance differences, or customer churn, using advanced statistical analysis and data segmentation.
Predictive Analytics: What Will Happen?
Predictive analytics uses machine learning, modelling, and trend analysis to forecast future outcomes. Whether anticipating customer buying behaviour or identifying sales hot spots, this insight allows for better forward planning and more precise resourcing.
Prescriptive Analytics: What Should We Do?
The most advanced level, prescriptive analytics, helps businesses decide on the next best action — whether that’s redeploying field teams, tailoring an offer, or fine-tuning a campaign. It turns forecasting into decision-making, helping CPM deliver measurable results for our clients.
Transforming Insight into Sales Impact
At CPM, we don’t just collect data — transform data into actionable insights.
Our data science experts work closely with clients to:
This insight is at the heart of how we deliver value through outsourced sales solutions. By aligning our actions with the data, we ensure agility, accuracy, and results.
What is the difference between data analytics and data science? Data science aims to predict potential trends, explore disconnected data sources, and find better ways to analyse information. Data analytics, on the other hand, is devoted to realising actionable insights based on existing queries.
Conclusion: Data Science Is Essential to Increasing Sales
Using data science to increase sales is no longer optional — it’s essential. Whether optimising performance in the field, enhancing customer engagement, or responding to market shifts, insight drives better outcomes.
By adopting a data-led, agile sales approach, businesses can unlock real competitive advantage — and that’s exactly what CPM delivers through our liquid approach to sales.
Ready to unlock insight and accelerate your sales? Let’s talk about how our data-driven approach can help.