6 ways for leveraging Big Data for your business

The amount of digital data in the universe is growing at an exponential rate, doubling every two years, and changing how we live in the world. Big Data is surely a big deal. We definitely are seeing an increase in activity with companies responding to the impact big data has made on their business.

Here are 6 ways that you use for leveraging big data for your business:

1. Create a team of experts.

Marketers must create a team of big data experts, big analytics experts and consumer, brand and category experts to build a solution that helps their business leap ahead of the competition. Ideally, this team includes three types of individuals:

Data jockeys: the starting lineup who can prepare and manipulate big data sets for analysis
Data scientists: the top draft picks who understand modern analytic methods and can build both simple and complex data models
Business consultants: the all-stars who can relate your company�?¢??s questions and goals to the right analytic methods

2. Create a project playbook.

Working together, your team should create a playbook -- either for ad-hoc analytic projects or for operational tracking and usage applications.

For major ad hoc analytic projects:

Once the business question has been defined and articulated, the first step for an ad hoc project is to be sure that the data (its source, accuracy and periodicity) is fully understood prior to its application. It is typically sufficient for a few individuals on the marketing team (e.g., marketing operations) to have a full understanding of the data. The rest of the marketing team (mid-level managers and individual contributors) only need a top-level understanding of it. Marketing executives need a more detailed understanding of the data usage and where the potential pitfalls might be in the context of the entire business.

For operational tracking and usage applications:

Marketing executives need a good understanding of the data here as well, trusting that knowledgeable subject-matter experts (marketing operations) have a deeper understanding of the data across all areas. This is especially important if operational tracking and usage influences major company decisions. Providing summaries of the data through easy-to-understand visualizations is critical for the marketing team to quickly understand data applications and swiftly make the right decisions. Lower-level marketers need a deep understanding of the specific area that they are operating in as well as a high-level understanding of other data and its potential impact on their area of operation.

3. Identify your end goal.

If your data and analytics aren't clearly aligned with an important business question whose answer leads to greater profit, brand recognition or market share, then the efforts and investments will be for naught. Getting this right (choosing the right play for the circumstance) is critical for success. Goals could include:

Using media data at a zip-code level to determine media coverage for the target population in a target zip code
Using geospatial temporal data to help retailers improve their share of footfall to known shoppers in their category
Using detailed consumer profile data to better target likely purchasers

4. Capture and track the right data.

Identifying, capturing and tracking the right data is the first step in building a credible data model. Many CMOs say their teams' biggest challenge is capturing the right online data. Web visits, email clicks and video views aren't always the best indicators of marketing success. Many new online data points are becoming readily available. Capturing and successfully utilizing them will allow your company to engage in highly valuable marketing tactics.

Here are a few examples:

Consumer geospatial data can increase consumer footfall to your retail, restaurant and branch locations and away from the competition.
Sentiment tracking helps to capture market perceptions of your brand based on an analysis of consumers' social media. Your brand can use this method to understand how consumer perceptions of your brand stack up against the competition.
Click tracking and advanced attribution can help your brand understand the sequence of clicks that brought a consumer to your website and led to conversion.
Search analysis helps brands understand which search terms are most relevant to your product category, helping your content management team craft SEO-friendly web copy, social media posts and other indexable content.

5. Apply the right analytic methods.

Once data has been captured, the right analytic methods need to be applied. Data analysis specialists can help identify the statistical or machine-learning method that is most relevant to your business, translating your company's big data into insights and operational value quickly and accurately.

Some of the analytic methods they might use include:Marketing mix modeling is used to optimize the marketing mix of media channels to generate the highest ROI.

Customer lifetime value is a great fit for companies that have a direct relationship with their customers. This method can help your business determine which customers are likely to generate the most revenue (with the smallest cost) over time.
Propensity analysis determines which customers are most likely to purchase a product within the next month.
Attribution analysis is mostly used for optimizing online media to determine which online marketing channel (e.g., search, social, paid digital) is most cost-effective to generate incremental revenue on a dollar-for-dollar basis.

6. Create clear directives and recommendations.

Be sure that your analysts can deliver outputs using easy-to-understand visualizations with clear recommendations on where and how to focus marketing investments and where to trim back.

Source: HOB

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