Set Your Sights High: 5 Steps to a Rock-Solid Data Cloud Strategy

Imagine you’re a detective on a complex case with clues scattered all over the place, held by different teams. Each clue is key, but when they’re all over the map, piecing together the whole story becomes a real headache. This kind of fragmentation can make you second-guess the reliability of your information and slow down your progress, much like businesses dealing with data spread across different silos, which makes it hard to trust the insights you get and act on them effectively.

But picture if you could solve this challenge by building a “central intelligence hub” that pulls together all those clues, no matter what internal system (Salesforce organizations or ERPs) or external system (data lake or warehouse) they’re hiding in, and unifies it in one place. With this clear, unified view, you can tailor interactions with customers, improve decision making, and power AI and automations with data you trust — kind of like cracking your case with flair and finesse.

Data Cloud, our hyperscale data platform built into Salesforce, makes this possible. Data Cloud brings together any data, from any source into the everyday workflows and applications across Salesforce. But the full potential of unifying and taking action on all your data can only be realized with a plan. The plan doesn’t have to be linear, but it should cover these five essential steps.

1. Set your goals – and make sure they’re measurable

As the author Stephen Covey famously said, “Start with the end in mind.” When you’re crafting a data strategy, it’s crucial to align it with your business objectives. 

Think about the broader goals of your organization. Are you aiming to improve operational efficiency through automation, improve customer experiences, or integrate analytics and artificial intelligence (AI)-driven insights into your decision-making processes? What data is not easily accessible, who are the people that need this data? What areas of your business are underserved? What challenges can data solve across lines of business like sales, service, marketing and commerce? 

Consider what is measurable as your brainstorm your goals. Our customers have been able to realize benefits such as increased cross-sell and upsell, improving customer retention, speeding problem resolutions times, and reducing costs with Data Cloud.

2. Craft use cases (and don’t be afraid to get creative)

Data Cloud can integrate nearly any data — from any source — into everyday workflows and applications. So let your imagination run free with possibilities to use unified data to transform your business. Possibilities like… 

• Improving sales prospecting by connecting your customer relationship management (CRM) data with external engagement data – like web interactions, marketing campaigns engagement, and social media activity –  to identify and prioritize the highest value prospects.
• Turning service into revenue opportunities by combining interaction histories with website engagement and e-commerce to help your service teams offer personalized product recommendations. 
• Boosting marketing conversion rates with AI-powered next-best-offers and personalized customer journeys.
• Offering contextualized commerce, including product recommendations, promotions, and tailored pricing to increase shopping cart value.
• Generating more accurate insights by grounding data in your AI, pulling in accurate information about customer interests and preferences from internal systems and external data lakes.

Think as big as you can and align the use cases with your business goals. You’ll be amazed at the innovation and efficiencies you can unlock when you can unify and take action on all your data in one central place. It’s a game changer.

3. Chart a realistic path

Complex cases aren’t cracked overnight, and if you try to make everything a priority, you’ll end up with no priorities at all. That’s why it’s essential to ask your IT and business teams to assess which use cases will have the greatest impact. 

We frequently advise customers to start with efforts that are straightforward to implement yet yield a high return on investment. For example, using Data Cloud to power a customer service agent to manage simple queries can quickly speed response times and free up service teams to work on more complex issues. Prioritizing in this way will help you pace your efforts, create momentum, and realize a return on your investment fast.

4. Evaluate what data you need

A guiding principle of Data Cloud is to make data accessible unified, and actionable, so you can trust it to power your entire business. It’s not about just gathering the data in one place – it’s about associating all the data from multiple systems and taking action from your CRM and other Salesforce applications. 

So it’s important to give careful thought to the data you want to integrate. Your business and operational goals should guide this decision. The necessary data might include a range of things, from transaction records and operational metrics to customer interactions, asset data and data that lives in different Salesforce organizations or enterprise resource planning (ERP) systems. 

Integrating the right data sets into your systems is foundational to your strategy’s success. So it’s wise to involve stakeholders from various lines of business — from sales and service to operations, finance, and IT — who understand the data’s relevance to business outcomes and can guide you to the most critical data sets.

5. Track your success

Data Cloud is an investment – and your stakeholders will want to ensure it pays off. And you will need to continuously measure performance to ensure that you are meeting your goals. So, be sure to incorporate measures for tracking progress into your plan. Key considerations should include:

• Business impact: Determine how Data Cloud contributes to measurable business outcomes, such as revenue growth, cost savings, or improved efficiency. Monitor key performance indicators to assess the overall impact of your data cloud on the organization.
• Data quality: Assess the accuracy, completeness, and consistency of data that is pulled into Data Cloud. Monitor data quality metrics to ensure reliable data-informed decisions.
• Innovation and agility: Measure how Data Cloud enables innovation and agility within your organization. Track the number of new data-driven projects and initiatives, the speed of data-driven decision-making, and the ability to adapt to changing business requirements. This will help you show Data Cloud’s impact.

Get started with Data Cloud

Watch a demo to see Data Cloud in action and learn more about what Data Cloud can do for your organization.