In today's data-driven world, the ability to transform data into actionable insights has never been more critical for success. According to HubSpot’s research, 36% of marketers say data helps them reach their target audience more effectively.
Data-driven decision making is used in almost all areas of business, especially marketing. Why building the right strategy will lead to solid ROI, doing so can be complex and time consuming. .
In this post we’ll help by covering:
- What Data-Driven Decision Making Is
- How to Build Data-Driven Decision Making Processes
- Benefits of Data-driven Decision Making
- Data-Driven Decision Making Examples
Data-Driven Decision Making Process
1. Define the objective.
Begin by clearly defining the goal or problem you need data to address. You’ll also want to determine how you’ll measure your success and key performance indicators (KPIs). You can also leverage strategies like SMART goals to ensure your goals and objectives are specific, measurable, achievable, relevant, and time-bound .
2. Collect and prepare data.
Gather relevant data from sources like internal databases, surveys, customer feedback, market research, or external sources. Clean and prepare the data by removing duplicates, addressing missing values, and ensuring consistently strong data quality. Then, use tools like dashboard, spreadsheets, or graphic software to transform the data into a usable format for analysis.
3. Analyze your data.
Use data analysis and data visualization to gain insights from your collected data.
Look for patterns, trends, correlations, and anomalies to understand the relationships within the data and identify potential opportunities or areas of concern.
Not an analytics pro? Tools like HubSpot’s Marketing Analytics & Dashboard Software can help you record and measure marketing performance data with built-in analytics, reports, and dashboards.
4. Interpret the findings.
Compare how your results stack up against your goals and objectives..
Identify key insights and draw conclusions based on the patterns or trends observed. Consider the limitations, assumptions, and potential biases that could have impacted the data and how that could affect the quality of the decisions made. .
5. Evaluate options for decision-making.
Identify a handful of ways you can respond to, or make decisions based on, your data.
Then, with tactics like cost-benefit analysis, SWOT analysis, or decision trees, compare the potential outcomes and risks of each potential decision, carefully considering different scenarios and trade-offs..
6. Make your decision.
Select the best decision option after considering youranalysis findings, goals, and any constraints.
Involve key stakeholders in the decision-making process, communicating with and gaining feedback from them to ensure alignment and buy-in.
7. Implement and monitor your next steps.
Implement the chosen decision and track its progress against relevant KPIs, milestones or other performance data.
8. Learn and iterate
Lastly, continuously assess and refine your strategy based on any new data and feedback.
Analyze the results, including successes and failures, and incorporate the learnings into future decision making.
Use a feedback loop to ensure data-driven decision making becomes an ongoing practice. This way, you can set the stage for continuous improvement and adaptation.
Benefits of Data-driven Decision Making
Different teams gain different benefits from data-driven decision making. In this section, we’ll go over how marketers, sales professionals, and service professionals can leverage data to their advantage.
1. Targeted and personalized marketing
How can you create great content or campaigns for people you don’t know?
With that question in mind, it’s not shocking that one-third of marketers say that the biggest benefit of data is being able to better target prospects.
Data analysis helps you understand your audience's preferences, behaviors, and demographics, allowing you to create highly targeted and personalized marketing campaigns. This leads to better engagement and higher conversion rates.
For example, if you have a global audience, you might want to know which social platforms are used abroad and cater campaigns on those channels to audiences in different time-zones. This way, your content meets them where they are.
2. Optimized marketing budget allocation
In uncertain economic times, marketing budgets are more scarce than ever. This is why 36% of marketers say one of the top reasons they leverage data is to justify their spend.
By analyzing data on marketing performance across different channels and campaigns, you can allocate your budget more effectively. This ensures that resources are invested in the most impactful areas, maximizing return on investment.
When you’re struggling to get budget, the same data can also help you determine where you might be spending too much, helping you reallocate spend quickly when tactics that once yielded ROI lose steam.
3. Improved campaign performance and ROI
Marketers, like those we surveyed above, know that data is power when it comes to developing and measuring key strategies and campaigns. By monitoring key metrics, you can make data-backed adjustments to optimize your campaigns or tactics for better results and higher ROI.
Not to mention, your data and findings could also spark ideas for new campaigns or initiatives.
“Data should be one of the first things you look at when brainstorming new marketing initiatives,” says Pam Bump, Head of Content Growth at HubSpot. “Even when I’m trying to come up with a completely new idea, I’ll look at past campaigns’ performance, use SEO or social listening dashboards to determine traffic potential, and sometimes perform surveys to ask prospects in my target demographic what they’d like to see.”
Bump isn’t alone, while 32% of marketers say strong data leads to ROI, 31% say it helps prove the value of their work — which can be vital to marketing budget, roles, and career growth In today’s economy.
4. Enhanced customer segmentation and targeting
Every prospect is unique. While you shouldn’t launch a giant campaign for each of them, the right data can help you break your audience into demographic or preference-based segments and cater your tactics to each group.
By leveraging data, you can segment your audience more accurately based on various criteria such as demographics, interests, or behavior. This allows you to tailor your marketing efforts to specific segments.
5. Predictive analysis and trend identification
You can identify patterns, trends, and emerging market opportunities by analyzing historical and real-time data.
Predictive data helps you stay ahead of the competition, adapt to changing customer needs, and make data-backed predictions.
6. Improved customer experience and satisfaction
Better understand customer preferences, pain points, and behavior at every touchpoint by analyzing data. You’ll be able to deliver a personalized customer experience, resulting in higher satisfaction, loyalty, and advocacy.
7. Continuous improvement and optimization
Data-driven decision making provides marketers with insights into what works and what doesn't. By continuously monitoring and analyzing data, marketers can make data-backed optimizations to your strategies, campaigns, and tactics.
How Data-Driven Decision-Making Benefits Cross-Team Alignment
Whether you're a marketer who doubles as a sales or service rep at a small company, an entrepreneur wearing all the hats, or focused on better aligning your campaigns with sales and service department efforts, it's important to know how data-driven decision making impacts the whole funnel (and can drive more connected experiences between your brand, prospects, and customers).
Data-Driven Decision Making in Sales
1. Improved Sales Targeting
By analyzing data, sales professionals can identify and prioritize your most promising leads. It also can help you determine when marketing tactics aren't generating interest from ideal buyers. By digging into sales targets, buyer persona and lead data, teams across your company can focus their time and efforts on engaging prospects with the highest likelihood of converting, resulting in improved sales efficiency, higher closing rates, and revenue attributed to your efforts.
2. Enabled Personalization
As marketers, we've seen how personalized campaigns can meet different types of buyers where they are (ideally, at the right place and right time to learn about a product). Data-driven insights also help enable sales teams to understand customers' preferences, behavior, and pain points.
Armed with this information, you can tailor your whole funnel – from marketing content, to sales pitches, and to customer solutions to specific customer needs, leading to higher engagement, better conversion rates, revenue, and even customer loyalty.
3. Increased team productivity.
Sales leaders can identify and share best practices with your team. By analyzing data on successful tactics, strategies, or approaches, you can learn from your teammates and replicate successful sales techniques, leading to improved overall team performance.
For example, HubSpot’s Sales Reporting & Performance Management Software enables you to track your sales team’s progress and performance. You’ll be able to report on pipeline revenue, track target attainment, monitor your team’s sales activities, and unlock additional rep performance with deep coaching insights.
How Data-Driven Decisions Boost Service & Customer Experience
1. Improved customer satisfaction
By analyzing data, service professionals can gain insights into customer preferences, behavior, and satisfaction levels. This helps you identify areas for improvement and deliver more personalized and tailored experiences, leading to higher customer satisfaction and loyalty.
2. Efficient resource allocation
Data-driven decision making helps you improve resource allocation by understanding demand patterns, peak times, and resource use. This ensures that resources, such as staff, equipment, or inventory, are allocated effectively, resulting in improved efficiency and cost savings.
3. Proactive issue resolution
By monitoring and analyzing data, you can identify potential issues or trends before they become major problems. This allows you to take proactive measures to address or prevent issues, resulting in faster resolution times and improved customer experience.
4. Enhanced service personalization
Data enables you to gain a deep understanding of individual customers, their preferences, and their history with their organization. This allows for highly personalized service interactions, tailored recommendations, and a more personalized customer experience.
5. Better customer insights
Data provides you with valuable insights into customer behavior, needs, and pain points. This understanding helps both marketers and service teams anticipate customer needs, offer relevant recommendations, and provide proactive content or support, resulting in a more seamless and satisfying customer experience.
Insightful tools can help you achieve this. With HubSpot’s Service Analytics tool, you can view reports on customer service data such as how your customers use your knowledge base, chat wait time, and customer satisfaction scores.
7. Continuous improvement
By collecting and analyzing data on service performance, you can identify trends, recurring issues, or areas for improvement. This enables you to make data-backed decisions to continuously evolve and enhance your service.
Data-Driven Decision Making Examples
WWF wanted to gain a deeper understanding of user behavior on their website to ensure the success of its “Earth Hour” campaign in 2020.
They used analytics tools, including CMS Hub and Marketing Hub to identify their most engaging content, enhance their content strategy across channels, and segment their user base to improve awareness for the event. Of course, this requires generating insights from data.
With data-driven tools and processes, WWF was able to better understand “users’ actions across our website, emails, and social pages, connecting the dots without having to rely on separate analytics tools for each channel," says the Digital Communications Specialist at WWF. This, in turn, enabled their campaign to drive nearly 9500 newsletter signups.
In 2019, the HubSpot Blog had driven thousands of Page 1 search rankings and millions of organic (or search-based views) annually. But, we wanted to be less reliant on Google algorithms (which can drastically change traffic patterns when tweaked)
Pam Bump (also quoted above), leveraged historical data from blog posts, email campaigns, social media posts, and backlink profiles to build a content strategy around non-search content (which we call non-organic content).
While the content strategy drove half a million views in year one, Bump continued to use performance data to further implement, refine, and scale it, without negatively impacting our winning SEO tactics.
Today, “Non-Organic” content annually drives well over 9 million views, thousands of email and social engagements, and countless high-authority backlinks (coincidentally boosts search authority and organic traffic).
Get Started With Data-Driven Decision Making
Data is powerful. Without it, you’d be making decisions in the dark. Get started with HubSpot’s analytics and reporting tools.