Sentiment Analysis W h i t e P a p e r

Abstract 1

Introduction to Sentiment Analysis 2

Standard Process of Sentiment Analysis 2

Business Problem: Decoding the Consumer Sentiment 3

How Can Sentiment Analysis Help Businesses? 4

Benori’s Case Study: Evaluating Customer Sentiment for a Major Food Aggregator 5

Limitations of Sentiment Analysis 9

Conclusion 10

CONTENTS

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SENTIMENT ANALYSIS

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This paper is aimed at providing insights on how organizations can leverage Sentiment Analysis – also called ‘Social Media Listening’ – to understand the perception about their brand in the market and redesign strategies to increase their overall brand reputation which will lead to higher revenue.

Today, consumers can easily express their satisfaction or discontent with any brand, company or product through social media, online forums, blogs and review platforms, which can greatly influence the generic public opinion.

Sentiment Analysis allows businesses to analyze the public opinion about their products or services, unlocking deeper insights contained within each of them. These insights, when studied meticulously and used appropriately, enable a business to make better informed decisions.

ABSTRACT

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SENTIMENT ANALYSIS

INTRODUCTION TO SENTIMENT ANALYSIS

SENTIMENT ANALYSIS: STANDARD PROCESS

It is crucial for any business to understand the consumer sentiment about its brand, products or services to achieve continual growth and success. Lately, there has been an exponential rise in the number of companies focusing on decoding the tone of the customer through their social media comments – positive or negative.

A highly competitive marketplace makes it imperative for players to capitalize the valuable business intelligence available in the social media reactions towards their brand, failing which they risk losing a significant portion of their sales.

Sentiment Analysis, also known as Opinion Mining, refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information from the source materials such as comments, tweets or any such text posted online.

Extraction of consumer

generated content like tweets, comments,

status updates, etc., by leveraging APIs of

different social media networks Analysis of

extracted content and creation of data

dictionary. Classification of content into different types of sentiments or

emotions

Application of Natural Language

Processing (NLP) techniques and

derivation of meaningful

insights

Cleansing of data to exclude vague linguistic

elements such as sarcasms, idioms and

metaphors, etc.

Execution of trend analysis and detection

of commonality in sentiments across

the content matter

1 3

2

5

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SENTIMENT ANALYSIS

Sentiment Analysis experts widely use the following steps:

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SENTIMENT ANALYSIS

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BUSINESS PROBLEM: DECODING THE CONSUMER SENTIMENT

Businesses, typically, seek knowledge about the reputation of their brand among customers. Most business leaders, marketers and managements are looking for answers to following questions:

What are the problems faced by the customers?

Which product attributes may be responsible for creating a negative sentiment among customers and hence, impacting sales?

What are the unmet needs of the customers?

What topics are currently trending that can be used for their own content marketing initiatives?

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SENTIMENT ANALYSIS

Enhanced Customer Experience

Companies can use Sentiment Analysis to inspect each product/service review and attribute a score to it reflecting its overall tone i.e. positive, negative or neutral. This allows the company’s customer service agents to identify and reach out to the customers with extremely negative opinions and so as to placate them for defusing the negativity at the earliest.

Insights on Brand’s Strengths

Based on the scoring process mentioned above, the positive reviews allow the company to identify actions, product features or other factors that trigger positive emotions among customers, so that the company can leverage it going forward.

Improved Online Brand Presence

Today’s customers are very active on social media and expect their concerns or feedback to be heard and replied to, almost immediately. Sentiment Analysis can help customer support teams to understand underlying customer emotions expressed in social media posts and react appropriately in lesser time than possible earlier.

Well-informed Business Strategies

For sustaining its customer base and further growth prospects, companies require business intelligence to continuously improve and meet customer expectations. Sentiment Analysis provides the required insights on customer preferences, helping the company redefine its business strategies.

Access to Market Analysis and Competitive Edge

Sentiment Analysis helps to discover latest trends and new business opportunities. It can provide information on whether the market is stable enough, if the brand is received well, what the competitors are doing and if there is any untapped opportunities. It also allows the company to create strategies to act ahead of its competition by predicting customer expectations and foreseeing trends

Better Brand Revitalization

Brands often undergo a revamp, in terms of their image and positioning among the customers to attract a wider customer base and boost their market share. Sentiment Analysis helps to quantify the customer perception about the existing brand and can provide objective intelligence that can support marketing campaigns such as rebranding, offers and/or discounts.

HOW CAN SENTIMENT ANALYSIS HELP BUSINESSES?

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SENTIMENT ANALYSIS

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Positive Positive

19% 18%23%33%

58% 49%

Neutral NeutralNegative Negative

Benori conducted a Sentiment Analysis study for a major food aggregator brand in India. The client wanted to understand its reputation in the market vis-à-vis that of its top competitor. Besides this, the client also wanted Benori to provide insights on the key pain points of its customers as well as of its competitor’s customers. The main objective of conducting this study was to leverage social media data for:

• a) Enhancing overall customer satisfaction

• b) Designing acquisition and retention strategies to increase market share

Sample of Sentiment Analysis conducted:

BENORI’S CASE STUDY: EVALUATING CUSTOMER SENTIMENT FOR A MAJOR FOOD AGGREGATOR

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Overall Customer Sentiment

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SENTIMENT ANALYSIS

Monday Tuesday Wednesday Thursday Friday Saturday Sunday

7% 33% 30% 15% 16% 13% 14%

50% 29% 24% 27% 42% 31% 36%

43% 38% 45% 58% 42% 56% 50%

Pos

Neu

Neg

Brand B

For both, the client, Brand B and its competitor, Brand A, customer reviews posted on Twitter were extracted and categorized into positive, negative and neutral scores. The above charts highlight how customers of both the brands expressed their opinions on the social media channel. The frequency of negative reviews for Brand A was found to be much higher than Brand B. Therefore, the client, Brand B, could gauge the competitive edge it had in terms of customer satisfaction.

SENTIMENT ACROSS WEEKDAYS

The analysis was further broken down by days of a week.

Monday Tuesday Wednesday Thursday Friday Saturday Sunday

14% 15% 15% 23% 21% 19% 15%

14% 35% 18% 31% 26% 6% 15%

71% 50% 67% 46% 54% 75% 70%

Pos

Neu

Brand A

Neg

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SENTIMENT ANALYSIS

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This analysis revealed that the customers posted negative reviews mostly over the weekends, which can be attributed to the high demand over these days. Additionally, the weekly breakup of the sentiment study was helpful in gauging the ROI of the brand’s major campaigns. The client provided its customers with offers like Buy One, Get One (BOGO) on Monday and the hike in positive customer feedback on Tuesday and Wednesday meant that the campaign had been well accepted by the customers. This insight would serve as the base for the client to design its future strategies and improve its brand share in the market.

POSITIVE MENTIONS ABOUT THE BRAND

Love

Love

50

67

61

53

46

39

18

10

47 34

23 22 20 19

Delivery

Delivery

Service

ServiceReligion

Best Good

Good

Happy

Restaurant

Delivered

Delivered

Brand A

Brand B

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SENTIMENT ANALYSIS

Positive reviews by customers can help a brand understand what works well with its customers. This knowledge can help the company position its brand better to attract more prospects and expand its business. Also, when customers write good reviews about a brand on social media platforms, it can bring significantly more traffic to its website, increasing its engagement and hence, conversions.

From our analysis of its brand mentions, the client learned that, although few, customers like the brand for its ‘restaurant members’ and ‘overall delivery services’. This information indicated that the that access to a wide range of restaurants provides the brand an edge over its competitor. Also, listening to customers who have a positive outlook for the brand can help the company in converting them into brand influencers.

NEGATIVE MENTIONS ABOUT THE BRAND

689

785

573

554

498

367

264

374

252

192

233

205

204

212

191

405

148

242

138

164

133

290

Customer Support

Customer Support

Food

Food

Delivery

Delivery

Refund

Refund

Time

Time

Delivered

Delivered

Restaurant

Restaurant

Money

Money

App

App

Worst

Worst

Executive

Executive

Brand A

Brand B

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SENTIMENT ANALYSIS

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This social media listening exercise also helped the client in identifying the key pain points mentioned by its customers. The top reason for customers to write negative reviews was customer support followed by food quality and delivery time. Although, the overall sentiment was less negative for our client’s brand as compared to its competitor, the frequency of negative reviews on customer support, issues related with money refund or deduction and, ease of app were found to be considerably higher. Therefore, the analysis turned out to be more than a study of words and helped the client in identification of areas of improvement.

Benori’s suggestions

Basis the biggest customer pain point identified, Customer Support, Benori formulated a recommendation for its client.

The customer service experience needs to be enhanced by

• Paying attention to all customer service issues and delivering instant support

• Being available across all touchpoints that customers prefer

• Addressing passive complaints to prevent a conflict between the brand and the customers.

• Managing the brand’s social media conversations, highlighting how it is actively listening to its customers over multiple touch points and is working extensively to address them.

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It is important to note that customer sentiment about a product or a brand may be influenced by many factors, for instance, a bad day at office can directly affect the customer’s patience and hence, impacting the review negatively.

Also, sentiments can change over a period depending on the consumer’s mood. So, it is highly advisable to conduct a Sentiment Analysis with a large sample of data. Plus, it can be difficult for an algorithm to understand sarcasm or ironic tones in the language while interpreting the sentiments in isolation. Therefore, rigorous training is required for the analytics model to be highly effective.

LIMITATIONS OF SENTIMENT ANALYSIS

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SENTIMENT ANALYSIS

Several studies on implementation of Sentiment Analysis, are available to brands globally to guide them through the process of gaining insights on their brand reputation. In this study, we have discussed in detail how brands can leverage social media listening to a) gain insights on the customer pain points and their unmet needs, b) understand their positioning against the competitive, and c) redesign their strategies to enlarge their market share. Brands should periodically conduct sentiment studies in order to stay in tune with customer needs and continuously improve service.

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SENTIMENT ANALYSIS

CONCLUSION