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We’re in the age of Big Data: small bits of information collected on a large scale, analyzed, and often, acted upon. Big Data can be something as small as buying a pack of gum or noting an excited hotel check in on Facebook, but it has big implications for businesses as well as individuals.

Big Data uses statistical tools and algorithms to determine sentiment, spot trends, identify problems, and more. There’s incredible potential for application in reputation scoring both for individuals and businesses, and while this may sound like the future of reputation, it’s already being used actively now. Colleges are identifying potentially at risk students, lenders are going beyond the traditional credit score, and businesses are using data to put out fires online before they have a chance to spread. These are just a few of the ways we’re seeing Big Data used in reputation today.

Now, and increasingly in the future, businesses and individuals will be rated, scored, and essentially summed up quickly using Big Data algorithms designed to read reputations. This information is and will be used to make important decisions such as hiring, lending, partnering up, and more.

Why Big Data Matters for Reputation Management

With the ability to collect, analyze, and track big data including social media posts, business trends, and other sentiments, it’s becoming easier than ever to determine reputation. It has both positive and negative impacts, offering businesses useful information about marketing, customer sentiment, and more, while often toeing the line on privacy for individuals — often without their knowledge.

Big Data is typically good news for businesses interested in better tracking sentiment and reputation on a large scale. On the other hand, individuals concerned with privacy may not be as excited to have their individual purchases, social media posts, and other activities scrutinized, analyzed, and boiled down to a reputation score. But like it or not, Big Data is here and growing, and it can have a major impact on your interests.

The use of big data has already proven to be positive for many businesses. Companies that use Big Data have productivity and profitability that’s between 5% and 6% higher than others. It also helps them spend their marketing budgets more effectively, as companies that use data as an essential part of their marketing and sales decisions typically improve their marketing return on investment by 15% to 20%.

Ultimately, Big Data forms a sort of social credit score for both businesses and individuals. In the reputation economy, businesses are judged by how well they treat customers (and what customers say about them), their corporate social responsibility, and more. Individuals may be scored by their associations with friends and colleagues, job changes, social media posts, even individual purchases. Big Data can be used to track and analyze all of this information, and even neatly compile it into a reputation profile.

Big Data matters to reputation management because now and increasingly in the future, data will be used to assess and shape your reputation and ultimately, be used for actions and decisions that really matter.

How We’re Using Big Data for Reputation Now

Big Data may sound like a trend of the future, but the fact is that it’s being actively used right now. Here’s how brands, lenders, educational institutions, and other organizations are currently putting Big Data to work for reputation:

  • Hotels adjust their rates based on reputation comparisons: Using software from IDeaS Revenue Solutions, hotels are able to track their reputations including social media data. This factors into the software’s pricing recommendations for hotels. The system determines the best available rates for rooms and allows for adjustment of prices using comparisons of a hotel’s online reputation versus that of their competitors.
  • Hotels use reputation data to improve: In addition to influencing pricing, reputation data is used to improve guest experiences. Sentiment, complaint trends, and other details are tracked so that hotels can identify strengths and weak points in their service and delivery.
  • China uses Big Data for its Social Credit System: China uses Big Data to score its citizens based on finances, social media behavior, criminal record, and more. By 2020, China hopes to have an assigned credit code for every adult in China.
  • Payment services develop spending habit ratings: Alibaba now rates the spending habits of users on the Alipay service, assigning a credit rating between 350 to 950. Lending and spending habits are rated, but small data decisions come into play as well. For example, buying diapers will score well, as it indicates responsibility.
  • Schools identify at risk students: Some colleges are using data to warn professors about students who may be at risk. Typically, students don’t know about the warning system. Students can be placed into categories including freshman or first generation student, and professors are alerted if a student has tried to take the class before.
  • New credit lenders use social media and other data points to approve loans: Traditional lenders will use FICO credit scores to determine an individual’s credit rating, but some new startups are using social data to assess lending risk. For example, Lenddo checks your Facebook to see if any of your friends are delinquent on a Lenddo loan. And Kreditech uses up to 8,000 data points to assess applications, including data from Facebook, Amazon, and eBay. On Kabbage, borrowers allow access to online payment accounts for sales and delivery data, and activity on Facebook and Twitter can improve creditworthiness as well.
  • Business use data online reputation monitoring: Companies are turning to data analytics to detect trends in online communications. Artificial intelligence looks for bursts of negativity and monitors opinion about their competitors as well. This can help stop social media crises before they have a chance to take off, identify a need for recalls, and more.
  • Companies are tracking partners and resellers: Increasingly, companies are using data points to find out how their partners and resellers are representing their brands online. They’re looking for pricing discrepancies, differences in consistency and quality, as well as unauthorized resellers.
  • Businesses determine stakeholder sentiment: Rather than using panels or surveys to find out how consumers and other stakeholders feel about a business, Big Data is being used. With Big Data, businesses are able to track conversations to determine true sentiment based on word of mouth reputation.
  • Businesses measure the impact of responses: Big Data can play a crucial role in measuring the performance of your crisis management strategy. It can used to see how your audience is responding to statements, what influencers are saying, and which demographics are saying what.
  • Businesses identify room for improvement: Using Big Data, organizations are able to identify small problems and issues that can be improved upon. Monitoring conversations can point out a bottle cap that’s tough to open, or a handy smart phone feature users love.
  • Emails are delivered or sent to junk mail: Using Sender Score, emails are rated with a number of data points to deliver your message to an inbox, filtered folder, junk mail, or spam folder. Senders are assigned a score that determines how likely email providers are to apply filtering criteria to your IP address.
  • eScores offer a snapshot of individual data: Combining credit data, property and asset records, demographics, purchase histories, and public records including bankruptcy, eScores offer a bottom line assessment of your reputation. This score can be used for decisions including hiring, promotions, insurability, and more.
  • Businesses track employees who steal: A data product, Esteem, offers a list of employees who have stolen from the workplace. This information is used by many major employers to decline job candidates with theft incidents in their past.
  • Businesses track the real time sentiment of multiple brands: Global giant Nestle has more than 2,000 brands. Instead of relying on surveys and testing Nestle adopted a monitoring center that listens to conversations and tracks real time sentiment for each of its brands.

How We’ll Use Big Data for Reputation in the Future

In the future, we can expect to see more companies adopting Big Data for reputation management. These are just a few of the ways Big Data will grow for reputation:

  • Better market targeting: Small businesses can use Big Data to better reach their qualified buyers. Essentially, they’ll use Big Data to zero in on potential customers that are most likely to make a purchase.
  • Employers
    may identify employees who are job hunting>
    : As an employee increases job hunting activity, such as a higher rate of LinkedIn use, employers may identify that they’re getting ready to leave the company, or unhappy with their current work.
  • Perks based on reputation: We may see businesses offering extras to those who are likely to positively influence their reputation data. For example, hotels may research an individual’s travel history to identify people who have brand loyalty, leave positive reviews, and share socially in a way they want to encourage by offering free room upgrades and other perks.
  • Businesses can better identify brand evangelists: With sentiment tracking, it’s easier than ever to point out who’s saying what about your company and identify — and reward — brand evangelists.

What You Can Do About Big Data Reputation Management

Big Data is here, and it’s growing, and learning how to manage your reputation along with Big Data will become increasingly important to maintaining a positive reputation both for brands and individuals. In addition to consistently building a positive reputation, here’s how you can start to work with Big Data to manage your reputation:

Big Data Reputation Management for Individuals

  • Keep your resume and credentials consistent everywhere: Data scoring systems may flag inconsistent resumes and other information with potential trouble, even fraud, that can have your job application pushed down to the bottom of the list of potential candidates. Something as small as making a mistake on your year of graduation, then fixing it later, can make a difference. Ensure that job titles match with each post, as well as degree names, employer names and locations, and more. Double check any information before you make an initial post, because once it’s online, it may be troublesome, and potentially dangerous to your reputation, to change it.
  • Be aware of how you interact with brands and organizations: Joining conversations or interacting online generates data that can be used to build a profile of your activity, sentiment, and more. For example, by liking a college’s new student page on Facebook and starting to interact, the college may get access to information such as your friends, how many friends you’re making on campus, how often you interact with them, and more — and this information may be paired with data like campus facility card swipes to build a profile.
  • Use discretion when posting online reviews: Reviews can damage the reputation of a business, but they can also hurt the poster’s reputation as well. Users who often post critical reviews may be scored with a negative sentiment.
  • Keep personal and work information private online: Conversations including upcoming trips, medical issues, legal matters, trouble at work, and more can be scraped for data collection and used to build reputation information. It’s best to keep this information private, whether that means developing a private profile or simply not discussing this information online.
  • Choose your references carefully: Individuals will increasingly be scored by the company they keep. This means individuals in your friends list can influence lending or hiring decisions, and colleagues can help boost your profile. It’s always a good idea to accept connections only from people you trust and respect.

Big Data Reputation Management for Brands

  • Learn how you can use Big Data: There are incredible opportunities for all businesses in Big Data, particularly in the ability to learn more about sentiment and other issues in communications. Big Data applications for businesses are numerous and can be used to influence positive change in any organization.
  • Monitor your Big Data reputation: Find out what they’re saying about you. Go beyond Google and Yelp to track the conversation on a larger scale. Using Big Data, you can determine what customers and other stakeholders really think — a tool that can be more effective than surveys or panels alone.
  • Prepare to increase your technical staff: As we continue to collect, analyze, and use Big Data and increase our use of data in the future, you can expect to need more help analyzing and reacting to all of this data. Your communications department in particular may need a technical boost to identify and use Big Data.
  • Develop reputation ambassadors: The need to spread positive word of mouth is more important now than ever before. Identify and support enthusiastic employees, loyal customers, and other potential brand ambassadors that can positively influence reputational data points for your organization.