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Big Data Business Intelligence Data Analytics Data Monetization

7 Ways To Grow Your Business with Data Monetization

It’s estimated that by the year 2020 revenues around the world for big data and business analytics are going to exceed $203 billion. With all this earning potential, it makes sense to want to get your business “in on it.”

One of the best ways to do this is with data monetization. After all, data is the new currency.

In the past, businesses in the information technology sector have always been deriving value from data. However, the ability to effectively use and monetize data is now impacting virtually all types of business.

This means that driving value from data is something you can implement in your own business strategy. What many people may not realize is that this process can be extremely challenging.

As a result, you need to learn some helpful tools and actionable steps you can take to monetize data for your business.

If you are interested in learning more, then keep reading.

1. Decision Architecture

When thinking about analytics, the majority of organizations want to know how their business is performing, along with what information is needed to answer various performance questions. While this can help to inform and to describe what is taking place in the organization, it doesn’t enable any type of action.

Instead, the goal needs to be to capture the decision architecture of specific business problems. Once this is done, you can build analytics capabilities to create a diagnosis that enables decisions and actions. Leaders need to focus on making decisions that are based on data, rather than just answering questions about what already happened.

2. Stop Revenue Leaks

Busy healthcare providers, clinics, and hospitals can easily lose track of the services being rendered. Every procedure has an assigned code and description. Each of these often includes errors.

By using analytics, the organizations can identify patterns associated with procedures and codes, flagging patient invoices for possible errors or even missing charges. Intelligent data use can also help the organizations improve the ROI of their collections process.

3. Data Aggregation

The method that is at the very bottom of the pyramid, but that represents the biggest opportunity to earn, is data aggregation.

This means taking data from various sources, including your business, and merging it together to create a larger, integrated picture. While the data sources on their own may be interesting, when they are combined, they become valuable.

An example of this would be your credit report. The information credit bureaus aggregate, such as the credit cards you have, if you have a mortgage, and if you pay your bills on time, can be sold for a profit.

By aggregating this information into a single report, the information can be sold to interested parties. While there isn’t a lot of money in this, it’s still money.

4. Infer Customer Satisfaction

Many organizations use social media and survey sentiment to understand the levels of customer satisfaction. By combining data from several sources, airlines can now infer how satisfied a customer is based on factors, like where they are sitting.

This process requires information to be aggregated from several sources. However, in the airline example, you can use the information to determine if a customer is going to fly with you again, and if not, offer a free upgrade or other incentives.

5. Embrace a New Revenue Model

Today, data is actively changing relationships companies have with customers. Manufacturers of tangible goods are now supplementing the products they sell with flexible software options and services to offer customers new choices and new revenue streams.

Additionally, these companies are providing much higher levels of personalization. Across several industries, new economic models are starting to be explored – like replacing an auto fleet with self-driving cars.

In this example, rather than selling data, people are going to pay you to solve a problem or to provide answers. This is a unique revenue model.

The value lies in the fact that you have married your data to the mission of a business and solving a problem that businesses have. This is what is going to generate revenue.

6. Detect Piracy and Fraud

Most online retailers sell products on several different websites. Supplemental sales channels typically include eBay, Amazon.com and other online marketplaces maintained by larger retailers, like Best Buy and Walmart.

Selling through these channels is extremely data-intensive, since the customer types, products, and pricing can vary greatly across the channels. In some case, the price discrepancies are so large that they signal possible piracy or fraud.

If you sell across dozens of e-commerce websites, then consider building databases of your own products and your unique pricing. You can then compare this to existing expected pricing data, allowing you to detect stolen goods or suppliers who are mispricing their goods.

With this information, it’s possible to go to the marketplace and make a report stating that they believe someone is selling stolen items.

How Can You Use Data Monetization Methods for Your Business?

Data monetization is an ever-evolving concept that offers opportunities to earn profits by providing information to others. Your business can take advantage of this by utilizing the tips and information here.

The fact is, there are already countless businesses, in all industries, that are currently using data monetization. Now is the time to begin doing so, too, as it offers huge revenue stream potential.

If you are convinced that data monetization is something you want to use for your company, then contact us. We can provide you with help and information about how this process works.

Categories
Big Data Data Analytics

How Social Media Data Can Boost Your Sales

Social media data is one of the richest sources of information available to modern marketers, influencers, website operators and data scientists. One of the challenges, though, is finding the right way for your operation to harness that power. Let’s take a look at how social media data can boost your sales.

The Raw Data in Social Media

There are plenty of ways to deploy data analysis tools to both mine data and derive insights from it. These include looking at data points like:

  • Shares and likes
  • Mentions
  • Hashtags
  • Click-thrus to URLs
  • Addition and loss of followers
  • Demographic groups
  • Influencer networks

It’s important to not obsess about the vanity metrics, though. All the followers in the world don’t mean much if they’re not translating into sales. For example, tracking codes need to be embedded with URLs to verify that social media followers are moving into the marketing funnel. By using embedded referral codes specifically designed for your social media presence, you can keep tabs on whether followers are converting.

Finding useful sources of data is also important. There are plenty of free options, such as pulling marketing data from:

  • Facebook Insights
  • Google Analytics
  • Twitter Analytics
  • LinkedIn Analytics

Some social media companies, such as Instagram, also offer paid access to their data. In many cases, however, it’s possible to pull data using other solutions, such as web scrapers.

If your setup is properly configured, you should be able to track engagement as it moves through your marketing funnel. For example, your Twitter-specific referral code will show up in both Twitter Analytics and Google Analytics, making it easier to tie user behavior to particular campaigns.

Developing Insights from Social Media Data

The best pool of information means nothing if you can’t use data analysis tools to derive insights from it. Foremost, you need to know what goals your business is shooting for. You can make a checklist that covers things like:

  • Acquiring new customers
  • Developing a more widely recognized brand
  • Making decisions based on social media data
  • Responding better to customer concerns
  • Fostering a superior customer experience

Let’s say your business wants to focus on social media as a way to quickly identify customer complaints. One great thing about social media is that folks quitting your brand might not call your customer support hotline to express their discontent, but you can bet they’ll complain to their friends online about your company’s products and services.

One way companies take advantage of this is sentiment analysis. This is a data-driven decision-making tool that focuses on gathering data regarding positive, negative and neutral statements that people make about companies online. By regularly scanning social media, these firms are able to “read the room” at a global scale. Instead of letting customer anger fester out of sight, sentiment analysis allows companies to get out in front of problems.

There is also plenty of information hiding in the networks that folks form on social media. Marketing data can be developed by creating network maps of their social associations. For example, a retailer that wants to build an influencer campaign on Instagram wants to know which users are going to spread ideas the fastest. They can then supply those Instagram influencers with:

  • Early access to product details
  • Marketing and brand materials
  • Product demos and samples
  • Immediate access to top-tier customer and technical support
  • Opportunities to meet with key players
  • Invitations to company-sponsored events

Driving Business Decisions

Using marketing data should not be seen as a one-way street. There’s a lot that can be learned by monitoring the social media sphere. Trend analysis, for example, can allow companies to get ahead of what people are excited about. A clothing company might focus on analyzing trends coming into each of the fashion seasons, allowing them to handle ordering issues like:

  • Choosing quantities
  • Conveying customer demands to overseas buyers
  • Establishing transport times to put products in stores in time for trends to peak
  • Re-ordering items that are expected to sell out

It’s important to develop a data-driven culture at a company in order to make the most of social media data. Stakeholders and decision-makers shouldn’t be stuck wondering what the social media budget is actually doing. By deploying dashboards, data scientists at companies can provide real-time, engaging insights to those parties. In no time at all, folks who once questioned data and social media expenditures will be checking the dashboards on their cellphones to see how campaigns are unfolding.

Building this sort of data-centric business culture requires an investment. Infrastructure has to be put in place to ensure data scientists on your team have the servers they need to pull data, clean it up, analyze it and generate insights. Done the right way, though, building out this sort of infrastructure can help you get a better grasp on how customers interact with your brands, products and services.

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