Manufacturing businesses have often mastered operational efficiency. Many already leverage data to streamline production, reduce waste and optimise supply chains. Yet, when it comes to sales and marketing, the same level of data-driven discipline is often missing. Too many rely on traditional, relationship-led approaches that don’t scale, leaving growth to chance rather than insight.
A growth data strategy changes that. It gives manufacturers the clarity to see what’s working – and what isn’t – across the entire revenue generating process. It pinpoints where in the pipeline attention is needed, identifies the right customers to target and reveals how to lower acquisition costs, reduce churn and increase share of wallet. In short, it applies the same rigour you’ve perfected on the factory floor to the front end of your business – where growth happens.
What is a growth data strategy?
A growth data strategy is different from a broad enterprise data strategy, which can span finance, HR and operations. Instead, it’s tightly aligned with the customer-facing parts of a business – the areas where data and strategy most directly drive growth, such as sales, marketing and customer service.
It defines how organisations:
- Attract new customers by unifying and enriching data from multiple sources
- Convert opportunities with insight-led, real-time engagement, which can be optimised with (governed) AI capabilities
- Retain customers by building loyalty through personalised service and journeys
- Grow accounts by identifying cross-sell and upsell opportunities
This targeted approach ensures data investments deliver measurable impact and ROI – driving business growth and optimising customer experiences.
Why manufacturers need a growth data strategy
1
It can reveal what truly drives growth
Investing heavily in sales and marketing without clear visibility into what’s working is a recipe for disappointment. A growth data strategy can help pinpoint the channels, campaigns and customer segments that deliver the best returns. This insight allows you to double down on high-performing tactics, eliminate waste and ensure every pound spent accelerates revenue growth, rather than disappearing into unmeasured activity.
2
It can ensure resources are focused where they matter most
Without data-driven insight, sales teams often chase every lead equally, wasting time on low-value opportunities. A growth data strategy shows exactly where deals stall and which accounts have the highest conversion potential. This enables smarter resource allocation, shorter sales cycles and higher win rates – turning your pipeline into predictable growth, rather than a guessing game.
3
Reduce churn and build long term customer value
Retaining customers is far more cost-effective than acquiring new ones, yet many manufacturers lack the insight to predict churn or deepen relationships. A growth data strategy enables you to identify at-risk accounts, personalise engagement and uncover cross-sell and upsell opportunities. For example, a global producer of chemicals and plastics partnered with Edit, part of Salocin Group, to unify fragmented data, enabling targeted retention campaigns that improved customer loyalty and increased revenue from existing accounts.
4
Preparing you to leverage AI
AI is transforming how businesses predict demand, personalise engagement and optimise pricing – but it’s only as powerful as the data behind it. Manufacturers that lack a unified, high-quality data strategy risk falling behind as AI adoption accelerates. A growth data strategy ensures your sales and marketing data is clean, connected and actionable. So, when you deploy AI tools, they deliver real insights and measurable outcomes, not noise. This is the bridge between today’s analytics and tomorrow’s automation.
How to build a growth data strategy
A growth data strategy needs to balance two key concepts:
- Actionable: the growth data strategy must identify key use cases for data that are directly linked to improvements that support growth – a backlog of use cases, prioritised to balance value and feasibility, is critical. Picking the right starting use cases, delivering value fast, and building stakeholder belief is essential to creating momentum.
- Sustainable: taking action without having an overarching vision is a recipe for chaos, initiatives being spun up all over, creating inefficiencies and eroding trust. The growth data strategy must therefore also identify the key foundational capabilities needed for long term value realisation from data.
To reconcile these two competing forces, you need to tackle your data strategy in a way that respects them:
- Link data directly to your growth metrics – identify key decisions, business outcomes or insights that directly drive growth and translate these into use cases that describe how data should support them being realised. Creating a strong backlog of use cases, quantified to cost savings, revenue generation, customer loyalty, employee satisfaction and other metrics, gives you a clear reason to believe and builds excitement across stakeholders.
- Assess your current capabilities – translating use cases into the capabilities they need is a key next step. You’ll find commonalities across use cases… maybe it’s a key people skill that is needed to speed up reporting builds, maybe there’s a key data source that if higher quality would enable multiple use cases, or perhaps it’s a critical technology. Identifying these critical capabilities, assessing the current maturity and defining a target state will help you hone in on what matters most.
- Build a roadmap – Once you have your use cases and a solid understanding of the critical capabilities that support them, you can start to build your roadmap. Classifying use cases by feasibility versus value will help you understand use case candidates for prioritisation, or foundational capabilities that, if tackled first, could unlock multiple use case benefits. The roadmap needs to create a strong link between capability workstreams (e.g. building certain foundational aspects) and use case value being unlocked.
- Think big, start small, iterate – Once you have your plan, it’s then critical that you aim to deliver value rapidly – pick the use case or foundational capability that will most directly generate value. Also, when picking the first candidate, it’s worth considering how you’ll use this to promote the value of the data strategy. You need early wins to capture hearts and minds and build advocates; aligning with an influential stakeholder who is the beneficiary of the data strategy is a great tactic. Essentially, we want to kick start a virtuous circle – success from data driving interest and data driving more success.
Get started with Salocin Group
At Salocin Group, we help manufacturers bridge the gaps between data, strategy and growth. Our services include:
- Quick-start assessments – identify the most valuable data and strategies for your commercial operations
- Data foundation audits – create the technical backbone for data strategy development and business growth
- Data governance and process design – ensure data (and AI) is usable, accurate and compliant
- Data roadmap delivery – build a clear, sequenced data strategy roadmap aligned to business goals
Manufacturers that align their customer-facing functions with a growth-focused data strategy don’t just reduce risk; they also accelerate growth. By focusing on data strategy development and building scalable frameworks, manufacturers can transform their data into a commercial growth engine.
Contact us to discuss how to get started building your organisation’s growth data strategy, ultimately leading to more connected customer experiences and increased commercial success.
