I recommend to get most the data from your tools to your data warehouse. Put in place data quality checks and implement and ensure to keep a good data hygiene. Build your reports from your data warehouse so you can have data from different platforms in your reports. Ensure to take the data from the source for instance for your leads or opportunities your source is your CRM, for campaigns it’s your marketing automation platform or you me various ads accounts, etc. Often QA the data in your reports to ensure it’s accurate.

When overwhelmed with data sources for marketing decisions, prioritize by evaluating the relevance of each source. Focus on data that directly impacts your marketing goals and aligns with your strategic objectives. Disregard sources that do not contribute to your key metrics or decision-making needs, and concentrate on those providing actionable insights and measurable outcomes.

Data relevance is the most important factor when it comes to data usage, second to its accuracy. Rank your data types by how important and how closely related they are to the desired outcome or marketing goal, and base your decisions on those that are highest in rank.

When it comes data. All of it is noise unless you pinpoint what will drive either “actions” or “results”. For most people this means “sales”. CPL: Cost per Lead CPQL: Cost per Qualified Lead CPA: Cost per action (could be appointment, option etc) The job of marketing is filter out the true interest or desire of a prospect or “stranger”. Knowing that not all leads are created equally. We want to solidify what makes a qualified lead a success and how many qualified leads equals 🟰 a sale or “success”. These are all data points that you obtain through actually putting your marketing to work. You can’t “buy” this data from a data bank. 🏦

In my experience to effectively choose data sources for marketing decisions, prioritize relevance, accuracy, and timeliness. Start by identifying the specific goals of my marketing campaign. Use data that directly impacts those goals, like customer demographics or purchasing behaviors. Evaluate each source's credibility; trusted sources such as Google Analytics, industry reports, or first-party customer data are generally reliable. Additionally, consider how recent the data is to ensure relevancy in fast-changing markets. Test small before fully integrating a new data source to measure its effectiveness. Finally, use tools that consolidate data sources for a more comprehensive understanding and easier management