Data-Driven Marketing: Best Practices and Strategies (Part 2)

Numbers don't lie, but those who share them often do. We have run into many marketers who claim to have data-driven programs when the reality is that they only track a few dozen metrics. They choose key performance indicators (KPIs) not indicative of success but success pre-cursors that are easy to obtain and manipulate. However, if you really want to achieve marketing/sales success, you need to adopt a practice where you live and breathe the numbers. A philosophy where another A/B test continually challenges every aspect of your program. A program where it is NEVER "good enough."

Prevail Marketing understands that if you want to be the best, you have to engage in activities nobody else is willing to do. You never take shortcuts. Every aspect of your marketing and sales program is always in flux because you are constantly challenging the success you have achieved. Prevail has the most comprehensive data-driven marketing program in the industry. While many agencies claim a data-driven approach, their programs are shrouded in secret that will not stand the light of day. They track some of the most superficial metrics that fail to tell the story or are simply vanity metrics that are easily manipulated to make them look good.

Our philosophy is borne under the doctrines of growth hacking. We track everything. The minutia and the detail give us a complete understanding of what is working and what needs to be improved. We can act quickly to ensure each campaign or initiative is fully optimized to increase sales, revenue, and profitability.

Part 1 of this series (Data-Driven Marketing—The Secret Sauce) discussed the benefits of running a metric-driven program. We could have summarized the entire blog by saying, "Increases in customers, revenue, and profitability." In today's article, we will discuss the best practices that should be employed and the framework for setting up a metric-driven program. We will share how Prevail Marketing runs its metric-driven growth programs in a future article.

Setting Up a Data-Driven Marketing Program

We have run data-driven marketing/sales programs for decades. While the framework for setting up each program is based on a well-defined process, no two programs are the same. Our method allows us to incorporate the variables and nuances required for successful outcomes. We will show this general framework but understand that the rollout is based to a large degree on the strategist's knowledge and experience. Any successful data-driven program requires two critical elements: the process and the people.

The Process

To set up a meaningful data-driven marketing/sales program, you need to begin by doing your homework. First, you need to be the consummate expert who thoroughly understands the market influences and mechanics of the industry, market, product, and competition. This deep dive must involve collecting baseline data not only for the brand but also for all of its competitors. This consists of collecting thousands of data points using over 48 third-party analytic tools that examine all aspects of marketing/sales.

Tracking all the data for the competitors is to understand what is working for them, which allows you to find a blue ocean strategy that allows our client to find cost-effective ways to acquire market share.

Choosing What Data to Collect

One of the biggest obstacles that often trip up those who want to start a metric-driven program is determining what data to collect. Too many people get confused about what to collect and are overwhelmed by the vast amount of data. The results are frustration and often the end of the program before it began. While Prevail Marketing now tracks over 400 KPIs monthly, this process was built over time. We recommend you build your program over time by testing new elements each month and building as you go.

Significant insights will be discovered each month, and the excitement of seeing how it can be turned into leads and sales will propel you to want to grow and expand your program.

Choosing Third-Party Tools

External data sources can be invaluable for understanding target audiences and offer insights into market trends, competitor performance, and customer sentiment. We use over 48 third-party tools (e.g., Google Analytics, MOZ, SEMRush, SimilarWeb, SpyFu, SEObility, WooRank, etc.) However, these tools can be expensive, and budget constraints will limit what you can do. So, focus on high-impact areas demonstrating the value proposition and creating significant ROI. Utilize free resources at the outset, such as Google Analytics. When you are starting, prioritize reliability and relevance. Evaluating the credibility of the information derived from these sources is vital to ensure that the insights generated align with the organization's marketing goals.

Ensure you utilize user-friendly tools, especially at the outset of your program. Nothing can kill a data-driven approach that is trying to work with a difficult-to-use platform.

How Often Should Data Be Collected and Analyzed?

The data collection is an ongoing and everyday process. It is the lifeblood of any data-driven program. You need to be strategic as some data needs to be cultivated and acted upon daily, and others will be reviewed monthly. Here is a guide to help you plan your program:

Paid Demand Spending (e.g., pay-per-click, display ads): The results are reviewed and analyzed several times daily.

A/B Testing and Optimization (e.g., email subject lines, call-to-action buttons, landing page designs, ad copy, creative content formats, and communication timing): Continuously test and optimize. The results are reviewed and analyzed daily.

Website Performance (e.g., page load speed, backlinks, on-page SEO, Heat Map Results) The results are reviewed and analyzed weekly.

Marketing Attribution (e.g., Tracking customer journey touchpoints, Identifying the most effective channels, Optimizing marketing spend, Understanding conversion paths, and Measuring campaign impact). The results are reviewed and analyzed monthly.

Quarterly Outcomes It is important that your data-driven marketing program deliver actual results. We recommend that you collect and review ALL of the outcomes and improvements achieved every quarter. Put the results on a tally board and challenge your team to improve upon this each quarter.

The People

Having highly talented people to operate the data-driven marketing program is not enough. To have a successful program, you need to foster a data-driven culture. Each person must develop a metric-driven mindset similar to that of a growth hacker. Developing this metric-driven mindset is key.

Invest in your people and build a data-driven culture throughout your organization. The mindset and process must be taught and led by example. Encourage your team to investigate and test items on their own. Each week, we set aside time for each person to share what they analyzed and tested above and beyond the shared goals. Watching their excitement and enthusiasm when they share the knowledge and insights they learned is incredible.

Not everyone has the ability to be a data-driven marketer. You need to hire specialized talent who loves sifting through data for insights and observations that tell the tale of the campaign. In many cases, your existing staff can be trained to understand the patterns and how to analyze the information. We recommend that more junior members of your staff partner with those who have shown a propensity to understand data analysis. Over time, they will evolve into experts.

It is essential to break down the silos and encourage cross-departmental collaboration. Data-driven marketing should not be limited to the marketing department alone. Share insights and collaborate with other sales, product development, customer service, and IT teams. Integrating data and insights from different business areas allows you to make more informed decisions and create a seamless customer experience.

BEST PRACTICES

The area of data-driven marketing is subject to vast experimentation through trial and error. However, when setting up and running the program, it is critical to understand what are best practices. This does not mean you don't continue to test and prod the boundaries, but you need to reconnect with best practices after such tests to ensure your program does not lose sight and results suffer. Here are some examples:

Artificial Intelligence (AI) and Machine Learning

As complex as the human mind might be, it is no match for the power of artificial intelligence and machine learning. These tools are ideally suited to automate the collection and analysis of large quantities of data. We use AI to collect and analyze the vast amount of data and provide recommendations for further testing or implementation.

Quality over Quantity

Prevail Marketing may seem presumptuous in prioritizing quality over quantity when we track over 400 KPIs each month. However, data quality is a paramount concern. That is why we often use several third-party tools to test things like on-page SEO. We have found that each platform has its own biases, and we use several systems for data validation. The nuances matter; you need to track down and understand any anomalous data point; we have our quality control team do this every week.

We have also established protocols that help protect the data's integrity by implementing data validation rules. We have a standardized process for collecting the data, regularly reviewing it for contamination, and scrubbing it accordingly.

Optimize Outcomes

How you use the information derived from a data-driven marketing program will determine your success. It is hyper-critical that the data be applied in a manner that will enhance the experience of the targeted personas who represent your ideal customer. Strive to utilize the data to improve personalization strategies and persona segmentation (e.g., improve persona profiles and segmentation based on behavior patterns, develop micro-segments for specific campaigns.)

Protect Data Privacy and Maintain Compliance

Set up guardrails to ensure you follow national and local privacy and data protection laws, including GDPR, CCPA, HIPAA, and other relevant regulations. Maintain transparency about data usage and, where necessary, provide opt-out options.

Create a Data-Driven Culture

Foster a data-driven culture by setting up a formal program for the training and development of your team. Encourage a testing mindset by rewarding those who excel or go beyond standard practices to drill down to find data that will impact a campaign. Encourage cross-department collaboration and encourage cross-functional teams that compete against each other for prizes and recognition.

Conclusion

Data-driven marketing is a journey, not a destination. It is never about just collecting data but how you analyze the information and the actions or campaigns you implement as a result. If you are new to data-driven marketing, start slowly by creating a strong foundation for the most critical elements. Then expand and grow your collection efforts while ensuring the integrity of the data. Embracing data as a core component of marketing strategy is no longer optional but a necessity for sustaining competitiveness in today’s marketplace.