Three Steps To Dealing With Data Paralysis

Be honest: do you know what you’re doing with all of your data, or does it feel like it’s just too much? If it’s the latter, you’re certainly not alone. As brands strive to determine what’s influencing people to love, like, or share their brand, data has become more important than ever before. Very simply - data can impact sales. 

Unfortunately, a recent survey from eMarketer shows that 44% of companies believe that the amount of data they have is just too overwhelming.  That’s a bad state for any company to be in—paralyzed by your own research.  This paralysis in organizations is causing atrophy in marketing campaigns at the same time that social communities are demanding conversation. 

Here are the three key steps to bring your data back to life and under control:  

1) Favor smart data over big data

New technologies and lower operating costs have made it possible to track and store vast amount of data. But you’re simply not going to be able to deal with all the masses of information. That’s okay: not all megabytes are created equal. Instead of thinking about “big data”, you need to start thinking about “smart data.”

There’s an easy litmus test to gauge smart data versus big data. Ask yourself: what purpose does this information serve in meeting customer needs and advancing the business? Smart data is about understanding the value that the information brings to your business, the quality of that data, and its completeness.

The value of a smart data strategy comes from linking all of the data across channels, touch points and product lines. When organizations collect offline and online data, they often do so separately and the data winds up staying in silos. That’s unacceptable. In order to obtain data that’s smart enough to give you the complete picture, you need to pull your disparate data sets together and tie them to a specific goal – what you’re trying to learn about your consumers.  

Smart data also means handling quality and completeness issues.  Data issues like missing values, missing linkages and data anomalies can impede your ability to harvest data and move the business forward. Know what data you can or cannot use and have a plan to deal with quality issues that will otherwise make your data dumb.

2) Use analytics to mine your smart data

Analytics transforms your data into actionable information that propels strategic decision making. It’s what helps you understand who your most valuable customers are, when they buy, what prices they pay, what triggers will make them buy more, and when they are likely to purchase from someone else.

In order to mine your smart data, you need to apply analytical models.  These models will help you predict customer response to marketing efforts and determine the outcomes of campaigns. Models based on customer segmentation and conjoint analysis allow you to sift through large swaths of data and bring focus to your marketing strategy. Web analytics models give you an understanding of how people interact with your brand and products online.

Work with your team to apply these analytical models and identify the 10-15 most important things you need to know about your customers. Focus on the information that helps you determine what they are likely to do next and how you can create value for them that builds your relationship with them.

3) Create a roadmap using data and analytics

You can’t successfully mine smart data and analyze it overnight. But you can get started by creating a roadmap to reach your business goals. Now that you’ve identified what kind of data you need, and have decided to apply analytics models, it’s time to conduct an audit of the processes, systems, tools, and talent within your organization. Identify the gaps.

Next, figure out what measures-of-performance are important to your company. How will you know that your data strategy has been successful? What metrics will help you reach profitability and revenue goals? Softer marketing metrics like web impressions and brand awareness, while important, should be connected to harder metrics like sales, revenue and profit.

Next, outline the pilot implementation of your data plan. You’re not going to be able to mine all of your smart data and analyze it at once. Start small with a pilot. Be prepared to make mistakes. More importantly, be prepared to re-evaluate what’s working and what’s not. It’s what we call “living in beta.”

Once you’ve seen the results of a pilot program, you’ll be able to better plan out the investments that your company will need over time. Take a look at how you can best align your company’s resources against your data needs – and what you need more of.

Ultimately, it’s important to remember that the end goal to any smart data plan is the same as every successful marketing strategy: provide value your consumers. In turn, they’ll provide value for your business.

1 comment about "Three Steps To Dealing With Data Paralysis".
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  1. April Wilson from Digital Analytics 101 LLC, January 31, 2012 at 9:54 a.m.

    Another reason for data paralysis that you missed is the confusion between reporting and analysis. I find that a lot of organizations are drowning in reports without anyone actually doing TRUE action-oriented analysis.


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