Online Reputation Management or ORM as it is popularly known, is the practice of monitoring the Internet reputation of a person, brand or business, with the goal of suppressing negative mentions entirely, or pushing them lower on search engine results pages to decrease their visibility.
Ever since websites like Mouthshut, Twitter, Complaint forums, Blogs and Social Media sites like Facebook, etc. (user created content) have come into existence, people can voice their opinion and make their displeasure known to anyone who is online. Consumers now make use of the Internet to get information about products, services and reviews in order to get the best deal possible. Also, with the growth of online users and the e-commerce consumer base in India, it has become increasingly important for brands to monitor negative publicity and if possible, resolve or suppress it to the minimum possible decibel. In other words, ORM is imperative!
So how does it work?
The information spread over the Internet is unlimited. From Facebook updates to individual tweets, from product reviews to lengthy consumer complaints over a forum! How is it possible to get complaints and sentiments of a brand from all these sources? Let take a look:
ORM Model 1:
The first ORM model is better suited to in-house built ORM softwares and gives a sneak peak into the working of a fully functional ORM mechanism. Firstly, the software is fed with all possible combinations of keywords that defines the brand/product. In this model, the in-house software pings Google Search Engine every 1 hour. As Google is the largest and best Search Engine, it utilizes tens or hundreds of thousands of computers to process billions of web pages and return results for thousands of searches per second related to the fed keywords. This action leads to posts from various sources over the Internet being collated.
These posts are gathered from sources like news websites, Facebook, Twitter, review sites, and consumer forums and are structured in a format ready to be worked upon by a manual “Tagger” who identifies:
- The Sentiment – Positive , Negative, Neutral (what the post says about the brand).
- The Subject or Summary – what the post is all about.
- Category – what aspect of a brand it takes about- Product, Service, Offers or a Brand Personality, etc.
- Profile of the Author – profile of the person who posted.
- Type of Site – whether it s a news website, blog, micro-blogging site or a review website.
One can also add few more fields to the ORM model to make the report more specific at the end of the day. The more fields the manual “Tagger” can fill, the better it is for marketing research and subsequent planning to improve the brand’s online image.
Once done, all the marked posts go into different software (since daily data is huge, one can only imagine how large the data would be for a month and a year/s). This other software holds the data and displays an array of information which the end user/company wants in the form of a pie-chart. Depending upon the information on how fields were defined and filled during the manual tagging process, the pie-chart changes accordingly based on the end user preference of what kind of data that he/she wants to see ranging from sentiments, sources to more specific information like user information and brand expectations.The negative complaints will be collated and sent to the client for feedback and what response needs to be posted against them.
This model is particularly good in getting the complaints from every source plus the advantage of an in-house software but fails to gel with the customer care part where it needs to be actively involved till the resolution of a complaint online.
ORM Model 2:
This model works on an out-house software like Radian6. So, most of the information gets filled automatically like source, author, summary and site type except category and sentiment which the manual “Tagger” decides.
This model is more focused on giving an appropriate response to user complaints and betters the brand image to the people who matter the most – consumers!
1. All users who post a complaint on the Facebook wall of the brand page without giving details will be redirected to customer care form on the Facebook and asked to send their unique identification (for e.g. a phone number, smart card no., etc.) Hence, the complaint resolution process will be taken offline.
2. All complaints are updated in the form, get updated in an excel sheet/Google doc and sent to the brand customer service team, who then start working on the complaint resolution and contact the customer for the same.
3. The Brand customer service team marks the complaints that are getting resolved to the customer’s satisfaction in the same doc, so the ORM team can go back and acknowledge the customer with a message.
4. The customers who have not given the ORM team responses are asked for the details and a token number is generated for the same.
The 2nd ORM model works in constant touch with the customer service of the brand which helps in –
1. Sentiment Improvement: Usually, a post goes within 24-hours to the author that helps in easing the sentiment and bettering the consumer-product relationship when the customer comes to know that his/her complaint is being heard.
2. Speed of Response: The ORM team is equipped with adequate and exhaustive FAQ that lists out turnaround times with FAQ responses – usually within 2 hours of discovery of a complaint.
3. Quality of Response: High quality of communication is maintained throughout the engagement. Answers by the ORM team to queries are specific and to the point. They go beyond an extent to prevent generic, standard answers to all questions.
In order to measure quality standards, the ORM team recommends the Brand itself to review all responses prior to posting and validation. This model works well for the co-ordination and customer service center tag-team response that it is based on for resolution of an online complaint.
As day by day brands are becoming more open, managing their online reputation is also a task that needs smart and sensible handling; remember the Vodafone faux pas last year? If you’ve handled ORM, do share the smarter ways or tips in the comments and I would be happy to engage.
Slider image courtesy: www.chnibs.com