Data is everywhere. We all have to deal with it, irrespective of our industry or sector. Every customer or donor transaction generates a data point. Simply collecting these data points cannot help you achieve personalization or derive value from your data. Data strategy best practices, when tailored to the needs of your organization, can deliver great value.
Data can serve many purposes. It can deliver insights, help you personalize your outreach, increase conversion rates, and deliver greater ROI. Furthermore, people are doing great things with data. Using “Data for Good” is becoming a growing phenomenon. So, the question is how can data help you?
Tom Monahan, Founder and Managing Partner of Norton Street Capital, recently shared insights on leveraging data to drive value and personalization at WE Prosper Summit 2019.
Read on to see how you can meet your organization’s goals through applying these data strategy best practices.
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Think of the last time you changed your mind about something. The process usually involves learning some news or receiving new data. You’ve learned something new that has led you to reconsider what you know. This means data is persuasive.
We’re all in the business of changing people’s minds. This could mean that they need to be convinced to give to your organization or to purchase your brand’s items. Your data strategy can help you accomplish this.
Clive Humby, British mathematician said, “Data is the new oil…” This means that data cannot offer value in its raw form. Like oil, it needs to be refined to deliver value. Furthermore, like oil, more value is accrued by the users of data than the owners of it.
So, how do you refine your data to ensure that it delivers value? Applying the core principles of strategy can help you derive valuable and actionable insights.
At any organization, the overall strategy needs to be:
These core principles are universal and can be applied to your data management. Thus, here are a few data strategy best practices to help you fulfill your fundraising or marketing goals.
Don’t simply focus on what you can do, but on areas where you can excel. Many companies can claim that they have unique data. While that may be true, does your data have broad applications?
If the data you collect is accurate and informative but very specific to your industry and even more so to your organization, it offers no value to others. This means that your data cannot be an added source in your revenue stream. Similarly, when you source data from other entities, you have to ensure that it serves the broader purpose of your organization and not just a single department.
Save, combine, and protect data in interesting ways. Any of these could prove to be advantageous.
For example, WealthEngine goes beyond industry standards when it comes to data protection. Our regularly audited SOC 2 Type II certification sets us apart from other wealth data analytics solutions. This certification ensures all of our users that no one can misuse or hack the data they are compiling.
Your data strategy could lie in combining your unique data with other data points. By doing so, you may be able to predict something that no one else can. While your data may be proprietary and well-suited to deliver insights to your organization, you can strengthen this even further with third-party data.
For instance, you may want to run a direct mail campaign. Your team already has a list of prospects and their addresses. You can make your campaign much more effective through personalization. Your team can add demographic and lifestyle data on these contacts through a wealth screening. Now, you are working with a broader picture of who these people are and what makes them tick. It is easier for you to deliver more impactful messages to them.
Your data strategy must create unique value. It is better to avoid broad, obvious approaches if you want your approach to be sustainable. Similarly, avoiding gimmicks to provide real value to your customers and donors will increase their LTV.
You could stand out by offering convenience, unique/intuitive bundling, economic benefits, or even emotional benefits. For instance, let’s say you are a university. Typically, you will have various departments collect data for their specific purpose. Admissions has data on incoming students, while alumni relations has data on graduates. Similarly, various academic departments have data on current students. These databases can often be silos. By unifying your database and creating a cohesive picture of all students and alumni, you will identify missed opportunities for cross-departmental collaboration.
How do you get a fair return on the value you create? You begin by defining what fair means to you. Any value return must benefit your customers, employees, and investors. You cannot choose to please only one of these parties as they all have opposing needs. Therefore, balance is key in your data strategy.
Finally, keep customer permissions in mind. There is a thin line between valuable and creepy.
Interested in learning more about Tom’s talk on data strategy? Catch a recap of his session from WE Prosper Summit 2019.
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