The challenge today for most organizations isn’t data about their customers and prospective customers but being able to use the data to make strategic decisions. In fact, most organizations have a sea of customer data.  And the more channels we give customers to use, the more data we generate. The point of your data efforts is to help you better understand your customers and then use these gained insights to make your company’s products and services more relevant.

It’s Not the Data That’s the Challenge; It’s the Analytics

Trying to capture and manage data that doesn’t provide value and foster decisions drains a tremendous amount of time and energy from the organization. So it’s not data that most organizations lack. What they lack is customer analytics. It is customer analytics that enables an organization to anticipate which high-value customers are at risk or what offer to make to a particular customer segment. The vast amount of available customer data makes analytics essential to business decisions.

According to Srividya Sridharan, an analyst at Forrester Research, most organizations need to address four things when it comes to data and analytics.

• Actionability: The results that customer analytics generates need to be actionable, giving marketers the confidence to make data-driven decisions.
• Timeliness of Insights: Insights need to be delivered in a timely fashion to the various constituents, or else the exercise is a futile intellectual pursuit.
• Delivery Format: There is also a need to deliver the analysis to relevant stakeholders in a format that is digestible, relevant, and visually appealing.
• Accuracy: Significant marketing decisions, such as new product innovation, channel selection, and marketing investments, are made based on customer data and analytics, and hence, there is a need to ensure the accuracy of results. This is often achieved through continuous testing and learning.

Make Your Data and Customer Analytics Efforts More Successful

There are three initial steps that are critical to making your customer data and analytics efforts successful:

1. An Executive-Level Analytics Champion:  Data resides in so many systems and organizations, and there are so many people accessing and using data, that to have a successful analytics strategy takes top-level support.  A key role of this champion is ensure the analytics strategy is properly aligned across the entire organization so everyone is pulling in the same direction and that there is a clear roadmap on how data will be used to achieve business results.
2. Invest In Talent That Can Translate Insights Into Business Action.  There are many people who have the technical training when it comes to math, but they lack the ability to know which data is important and the business skills that help them see the relationship between the analytics and the business.  Developing business-savvy marketing scientists means investing in your analytics people beyond their technical skills.  Ideally, you want analysts who can use the data to tell a business story.
3. Make Your Organization Data Literate.  Over time, you want an organization that is literate in data and analytics.  This will most likely require having analytics groups integrated into the various lines of business, as well as tools that give non-technical users the opportunity to work with data. An data literate organization invests in tools that allow business people to use data to drive decisions.

It may not be possible for an organization to implement all three of these steps right away, which is why it may make sense to leverage third-party experts to help fill and close internal gaps and skills. Select third parties who can help you develop a roadmap for being able to leverage customer analytics in-house.

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FAQ:

• Actionability: Results must be actionable—giving marketers confidence to make data-driven decisions.
• Timeliness of insights: Insights must be delivered quickly enough to be useful; otherwise the work becomes an intellectual exercise.
• Delivery format: Analysis must be delivered in a digestible, relevant, and visually appealing format for stakeholders.
• Accuracy: Because major decisions (innovation, channel selection, investment) depend on analytics, results must be accurate—often achieved through continuous testing and learning.

1. Secure an executive-level analytics champion: Because data lives across many systems and teams, successful analytics requires top-level support. The champion ensures alignment across the organization, clarifies how analytics will be used to achieve business results, and establishes a roadmap.
2. Invest in talent that can translate insights into business action: Technical skill alone is not enough. Organizations need business-savvy analytics talent—people who know which data matters, can connect analysis to business priorities, and can tell a clear business story with the data.
3. Build a data-literate organization: Over time, aim for broad data and analytics literacy. This often requires integrating analytics into lines of business and providing tools that enable non-technical users to work with data and use insights to drive decisions.

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