Offer Management Using Sentiment Analysis, is the concept of applying knowledge from Sentiment Analysis in recommending suitable offers for customers. We do need to understand Sentiment Analysis, before we start to understand how it applies to offer management.
Sentiment Analysis is also known as opinion mining, and is the process of determining opinion (Sentiment) from a source material about a particular topic.
Source for Sentiment Analysis
The source for Analysis maybe be blogs, websites, articles, social networking sites and much more. Let us use a research by Vivid Social Research Division. As of January 2016, in Australia, the number of users reported for the sites were Facebook-15,000,000, LinkedIn-3,700,000, Twitter-2,80,000 and BlogSpot-2,450,000. All these users, contribute with their thoughts and opinions, and are a significant source of data for Sentiment Analysis.
The concept of proposing a customer with a promotion from the business, which, will appeal to his/her interest, and engage him/her to opt in for the promotion is Offer Management.
Offers & Predictability
Most of the information I present here are considering the banking business. Also, the same knowledge maybe applicable to other industries.
The banks make offers to Individuals, on basis of their risk ratings and his/her relationship with the bank. These types of offers, fail to consider the prevailing socio economic situations, within the individuals geography and hence, most of the time fails to interest. Which, brings us to a questions like, “Can this be addressed?”, “Can we really predict outcome of offers?”.
Yes, except a few cases. The likelihood of an individual accepting the offer is determined by various criteria. A few of these criteria can be the individual’s preferences, market outlooks, herd behaviour or recommendations by financial institutions, advisors, friends and family. Hence, if we analyse this information we have a very high chance of predicting the outcome.
Sentiment Analysis & Offers
Sentiment Analysis can help assess some of the criteria mentioned above and influence the presentment of an offer. Assume if opinions reflect in multiple blogs, articles, social networking sites, that real estate are at their lowest and hence it is the best time to buy a home. In such a situation, there is a higher chance of an individual to accept a home loan offer, rather than a mortgage loan. Because, in a situation when the real estate prices are low, a mortgage will yield his property a lower value than usual.
Let us consider another example, of an individual who liked a post. One, mentioning a credit card giving extra travel miles on spend, and he did not do so for a card with 2x reward points. It signifies that the card offering extra miles interest him more. The chances of him accepting a credit card offer for the travel card is higher than the rewards card.
The world is moving at an unprecedented pace, hence people have less time to spend on their banking apps. Due to which, the number of offers they will skim through is relatively less. Also, the situations in which they will have to visit a branch, or a representative is even less. This is forcing banks to capitalise on every opportunity they get to engage with their customers. The Sentiment Analysis based Offer Management will go a long way in ensuring that the customers get appropriate offers. Which, also considers prevailing socio economic conditions and market trends within their geographies. This will ensure focus on customer engagement and result in more converted offers for Banks .
Statistics compiled by SocialMediaNews.com.au for October 2016. Stats and research produced by the Vivid Social – Social Media Agency. Figures correct as of 31/10/16.
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