Cannabidiol (CBD) is a compound extracted from the cannabis plant such as Hemp and Marijuana that possesses both therapeutic and medicinal properties. In recent years, the interest in CBD has significantly grown across the globe. This upsurge in the public interest has led to the emergence of many brands, and online communities focusing on adopting CBD products. In fact, the global CBD market is projected to reach USD 15.3 Billion by 2025 with a CAGR of 22.2% between 2019-2025. With 2020 coming to an end, when we look back at such a tumultuous year, we can identify five top trends observed in the CBD industry.

Key CBD Benefits

CBD is considered as a wonder drug with varied and extensive medical benefits. From pain management and helping with psychological disorders to treating severe diseases like Cancer and Cardiovascular Diseases, CBD is currently used in treating various medical issues. The following are some of the proven uses of CBD.

Psychological Benefits:

CBD helps to relieve psychological disorders such as Anxiety, Depression, Obsessive-Compulsive Disorder (OCD), Post-Traumatic Stress Disorder, and Insomnia.

Physiological Benefits:

CBD is beneficial in treating Seizures, Nausea, and Cardiovascular disorders. It also assists in Pain Relief,  Reducing Inflammation, Lowering the Risk of Diabetes, Fighting Cancer, and combating Neurodegenerative Disorders.

 

Trend Analysis Methodology

We leveraged our proprietary Social Listening tool for this Trend Analysis. This tool automatically collects customer conversations from various online sources such as social media, blogs, e-commerce sites, and discussion forums, thus reducing the margin of error due to the larger sample size that helps in less biased and accurate insights. The mined unstructured textual data gets further processed by text mining and natural language processing (NLP) algorithms in performing multi-dimensional sentiment analysis to provide the below-emerging trends in the CBD market.

 

Emerging CBD Trends

CBD Edibles

Although the most common forms of CBD include oils, tinctures, capsules, and topicals such as balms and creams, CBD beverages and edibles have gained a lot of popularity in recent times. With increasing demand and popularity, CBD is now infused in a variety of food products such as gummies, protein bars, beverages, candies, and dried fruits to make it tasty, discrete, easy to consume, and attractive for the increasing customer base. As CBD edibles are broken down slowly in the digestive system, the CBD is released gradually over a more extended period thus, extending the effects for the consumer.

Source: https://mms.businesswire.com/ 

Legal Relaxations

At the tail end of 2018, The Farm Bill passed by the US Government legalized the production of Hemp, and it had a limited implication on the CBD industry due to fuzzy federal and state laws, which contributed to substantial growth in CBD production and consumption in the US. Also recently in Dec 2020, based on a series of World Health Organization (WHO) recommendations on cannabis and its derivatives, The United Nations Commission on Narcotic Drugs (CND) removed cannabis from its ‘most dangerous drug’ category recognizing the medicinal and therapeutic potential of the drug. Over the years cannabis products have found wide acceptance in countries such as the US, Canada, Spain, Germany, Uruguay, Australia, Columbia, Chile, and Israel. Many more countries anticipate the legalization of cannabis across various domains.

 

Continued Price Drop

Increased production due to the legalization of hemp has enabled a steady supply to meet market demands. This surge in availability of hemp, the raw material of the CBD, has led to a price crash in May 2019. Since then, the price of CBD has continued to decrease. As tracked by The Jacobsen, a price reporting agency, the average selling price of CBD isolate was at $4,000 per kg in July 2019 to ~$750 in July 202 – a drop of roughly $3,000 per kg in the last two years.

Expanding Research Areas

Research continues across the globe to uncover the potential uses of CBD, particularly in the areas of effectiveness to treat physiological or neurological conditions. The presence of a nonaddictive component that interacts with our body’s serotonin receptor has captivated the interest of researchers in studying it as an effective treatment for pain relief. The trend of exploring CBD as a potential cure for cancer due to its anti-inflammatory and antitumorigenic properties also continues. The antipsychotic property of CBD is also actively explored in treating mental conditions such as social anxiety and depression.

 

Certificate of Analysis

With a lack of specific industry regulations and standards surrounding CBD products, it is challenging for customers to know the precise composition of each product in the market. A Certificate of Analysis (COA) could help customers overcome this challenge. A COA is a document that’s issued by an accredited laboratory that certifies the complete composition of a product accurately. Lately, CBD brands have begun offering COA to their products as a common practice to win the trust of their customers. For CBD products, a COA is stipulated to include a comprehensive list of cannabinoids, terpenes, microbiological levels, and likely contaminants such as pesticides, solvent residue, or heavy metals.

While in hindsight understanding and adapting to trends will help brands stay competitive. The key to garner exponential growth can happen through predicting future trends in the least possible time. SetuServ’s VoCIS platform enables this through data-driven analysis at scale.

SetuServ’s VoCIS platform provides emerging trends,  customer insights, and market intelligence for the CBD and cannabis industry. It leverages AI technologies such as social listening, text mining, and sentiment analysis to provide accurate insights automatically.

 

 

Cannabidiol (CBD) has become one of the most emerging segments in the medical market and has captured the attention of the global consumer market within a short period. Constant shifts in customer needs and regulatory changes have made CBD one of the most dynamic market landscapes causing challenges for companies. With a significant consumer interest, CBD is turning it into a multi-billion-dollar industry on its own. Considering this strong consumer interest, if CBD companies or marketers manage to understand customer needs, strategize accordingly, and to leverage market opportunities. Before discussing in-depth on generating market insights, let’s discuss CBD and its benefits in detail.

What is CBD?

Cannabidiol (CBD) is the second most prevalent Cannabinoid, a type of chemical component extracted from Cannabis, a genus of flowering plants such as Hemp. The most popular Cannabinoid extracted from Cannabis is Delta-9-TetraHydroCannabinol or THC. Though both CBD and THC interact with the cannabinoid receptors in the body to treat various conditions, the lack of psychoactive effects is what differentiates CBD from TCH. In simple terms, THC mostly extracted from Marijuana, has intoxicating effects, whereas CBD is unlikely to cause such hallucinatory effects.

How CBD Products Works?

CBD produces effects in the body by interacting with two types of Cannabinoid receptors produced by our body, which form part of the endocannabinoid system.

CB1 receptors are present throughout the body, particularly in the brain. They co-ordinate movement, pain, emotion, mood, thinking, appetite, memories, and other functions.

CB2 receptors are more common in the immune system. They affect inflammation and pain.

CBD stimulates these receptors so that the body produces its own cannabinoids, known as endocannabinoids.

CBD Benefits

Growing research and development activities in recent times have helped in identifying the potential use of CBD in treating chronic pain, arthritis or joint pain, anxiety, and depression, PTSD, migraine, etc. While initially, CBD products were only available in oil form, now they are available in various edible formats such as drinks, bars, gummies, syrup, candies, and cookies. One new emerging trend is CBD infused food which has been catching up as a hot trend among chefs since 2019.

CBD Market

Based on a recent report by Grand View Research, the global market for CBD was estimated at USD 4.6 Billion in the year 2018 and is expected to reach USD 15.3 Billion by 2025 with a CAGR of 22.2%.

The market is highly competitive with continuous product and technological developments. Key factors driving the market include growing awareness of the merits of CBD, such as anti-inflammatory properties and other psychiatric benefits.

Understanding CBD Market and Customers

Customers drive the industry forward, especially when it’s an emerging market such as CBD. It is critical for businesses to understand their current and prospective consumers to be first to market while also capturing the consumer at their peak interest. As the market is still evolving, most brands tend to use their own customer data within their respective geographies such as sales and survey information to make market decisions. However, with limited sample size, this data is not truly representative of this rapidly moving market and can be inefficient in producing insights that would drive the brand towards success. Gaining a more global perspective on trends in the marketplace can help guide companies on growth trends and what’s to come.

Having data-driven insights on customer expectations is the key to CBD brands in developing marketing and sales strategies to prevail in this dynamic market. With the massive influx of consumers sharing their experiences using CBD products online, brands can leverage this data to understand ever-evolving customer expectations and pain points.

SetuServ’s VOCIS platform provides customer insights and market intelligence for the CBD and cannabis industry globally. It uses a proprietary text-mining algorithm that’s capable of extracting relevant customer conversations from online sources such as social media, e-commerce websites, blogs, and discussion forums. Insights can be viewed by various filters including geography, form, product, brand, etc. The platform employs AI-powered natural language processing (NLP) and sentiment analysis algorithms in uncovering deep insights on customer needs and gaps between customer expectation and realization. Combining these automated insights along with human SME intelligence, CBD insights helps brands to better understand the market landscape and navigate market challenges.

 

HCPs are becoming increasingly active in expressing their opinions on social media and online research publications. As Wall Street Journal noted in this article, this is driven by their desire to provide credible information online to help people stay updated with the latest developments in research and healthcare, especially during this Covid-19 crisis. For example, Bob Wachter, the chairman of the department of medicine at the University of California, San Francisco takes at least 2 hours of his busy schedule on most days to put out content on Twitter.

Our own research has shown that physicians have become quite active across a variety of social channels. From a random sample of 1,000 hematologists, we found that ~40% of them are present on at least one of the online platforms.

As the following example of Dr. Anthony Mato (an opinion leader in Hematology) illustrates, Hematologists are not only active with research publications in Pubmed/Clinical Trials.gov, but also in social media channels such as Twitter, Facebook, and LinkedIn.

Efficient pre-call research using this social data

These research and social posts published by physicians are valuable sources of insight for Pharma companies and their sales reps.  Many HCPs feel that the sales reps tend to be delivering a scripted pitch about the product and do not give details about new studies or data which support the need for using the product. To overcome this immense challenge, it’s critical for the reps to personalize the sales details to suit the specific interests of a physician. By researching a physician’s social and professional posts, sales reps can understand the top of the mind needs and concerns of HCPs, and tailor their pitch accordingly.  

Our PharmaSignals platform helps sales reps by consolidating conversations across channels and sending them via email. Sales reps can use this to identify conversation starters of interest for the HCP. Below is an example of a weekly email that is sent to a sales director that is currently using our platform.

Our PharmaSignals platform reduces the manual effort of tracking each of these targets across various social media platforms and media sites. Thus, giving readymade access to their content and increasing the chances of having better conversations with HCPs.

Businesses today have evolved from being solely brick and mortar stores to extending their offerings across multiple digital channels. With the increase in internet and smart device penetration, digital channels have become the primary touchpoint for customers to interact with brands. This distancing from in-person brick and mortar stores might seem like customer connections have diminished, however with the omnichannel and ubiquitous digital presence, businesses are now interacting with customers more than ever. This online relationship with customers has also enabled the brands to track and measure each and every interaction in the realm of cyberspace, thus more accurately predicting and delivering what their customers want. 

The abundance of customer data might sound like a big boon, but it also poses a particular problem to be solved – access and analysis at scale. With more than 80% of the customer data unstructured, semi-structured, and textual in nature, it’s quite challenging to process and extract insights compared to structured data. However,  text analytics presents itself to be an apt solution to overcoming this problem. In this blog post, we explore how text analytics helps customer experience (CX) and marketing teams attract, engage, and satisfy customers while staying ahead of the competition.

What is Text Analytics?

Text Analytics/ text mining is an Artificial Intelligence (AI) technology that leverages Natural Language Processing (NLP) algorithms to convert unstructured and semi-structured textual data into normalized structured data that’s suitable for analysis.

Source: Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications - Book

 

 

Use cases in which customer experience and marketing teams leverage

Text analytics has a wide range of applications and can be applied anywhere where unstructured textual data exists. The following are some of the key use cases where text analytics comes in handy.

Text analytics for marketing teams

It is quintessential for the marketing teams to understand the customers deeply in order to acquire, engage, and delight customers. Marketing teams also need to be aware of the customer pain points, ways customers perceive the product or service, and crucial factors influencing their buying decisions. In order to access customer insights,  marketing teams conventionally rely on methods such as surveys, interviews, and feedback. However, these methods are prone to bias and error that makes them inefficient. To overcome this, the application of text analytics enables marketing teams to access customer conversations from text-based data sources such as social media, discussion forums, and blogs, and transform them into useful insights to boost customer satisfaction and revenue generation.

Early customer trend detection

With the rise of social media and other digital mediums, customers share more of their daily lives online. This abundance of customer data can help businesses identify emerging trends. Uncovering these emerging trends provides brands new opportunities and an edge against their competitors. Text analytics serves to ingest a large volume of online data and identifies customer trends or emerging brands that could become a threat to the business.

Voice of the customer report

The voice of customer report provides a comprehensive, yet granular, view of customer sentiment and emotion related to a brand, product, or service. These insights help in improving customer experiences, increase revenue and drive customer engagement. However, tracking the triggers that influence customer opinions about brands, products, or services across various touchpoints is challenging. Text analytics facilitates the analysis of customer conversations and feedback from various online sources and serves them up as useful data and insights at scale. These insights guide the marketing team to strategize campaigns for better output and engagement.

 

Text Analytics for Customer Care Teams

Customer experience teams are often inundated with high volumes of customer communications on any given day. With a magnitude of textual data involved, CX teams often leverage text analytics to automate repetitive tasks and identify areas to improve Net Promoter Score (NPS) and other customer satisfaction KPIs.

Conversation analysis

The internet has become the predominant medium for customers to communicate with businesses via multiple modes such as emails, support tickets, social media, and chat. These customer conversations provide a wealth of insights for understanding customer needs and contributing to business growth. Applying text analytics enables us to analyze customer interactions and communications at scale to find data-driven insights that highlight critical customer issues and improve customer experience.

Automated ticket prioritization and routing

Customers expect and value timely, effective, and personalized customer service interactions. However, businesses are falling short of resources and efficient workflows in place to handle customer queries efficiently. Managing a high volume of customer queries can be challenging as manually tagging tickets and routing them through the right human agent is a time-consuming process prone to errors and may also create bottlenecks and delayed response times. However, text analytics can automatically categorize the support ticket and assign it to the most suitable pool of agents. In addition, with sentiment analysis, the systems can determine the urgency of resolution based on the tone of the customer communication and prioritize the tickets.

 

SetuServ offers a variety of text analytics solutions or companies that want to support growth while maintaining a strong customer connection.  Our methodology combines Artificial Intelligence (AI) & Human Intelligence (HI) to provide accurate insights. SetuServ’s Voice of Consumer Insights and Signals (VOCIS) platform serves a majority of industries with offerings across departments For much more complex and industry-specific solutions, SetuServ offers custom AI solutions based on the specific customer use cases.

The COVID-19 pandemic continues to impact most industries at an unprecedented scale globally, and the health and wellness industry is no exception experiencing significant disruption over the past few months. Due to the ongoing pandemic, the customer’s priorities have shifted towards physical wellbeing. This change in customer preferences poses a monumental challenge to the health and wellness companies in navigating this crisis. Before discussing the top health and wellness trends in 2020, let’s touch upon health and types of wellness.

WHO defines health as a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity. Whereas according to The National Wellness Institute, wellness is a conscious, self-directed, and evolving process of achieving full potential.

Top 5 health &wellness trends of 2020

1.Adoption of digital wellness products

The global digital health market size is expected to reach USD 385.8 Billion by 2025. As the physical world comes to a standstill due to COVID-19, the adoption of digital health and wellness solutions have surged. With many stuck at their home and yet wanting to improve themselves, digital wellness products such as meditation apps, digital fitness classes, and online healthy food tutorials are booming. At the same time, most of the global workforce is working from home full-time for the first time and has led to anxiety and stress that has impacted overall wellbeing and productivity. 

In order to balance business continuity and employee wellbeing, organizations have implemented mandatory digital wellness programs to help in improving the wellness and productivity of their employees.

2.Greater focus on mental wellbeing

The fear of contracting the virus, significant changes to everyday life, job loss, etc has induced anxiety and other mental illness to a greater extent. The new realities like social isolation and temporary unemployment are a few additional factors that have significantly contributed to the rise in mental wellness. Though this issue has created a surging demand for home-based over the counter sleeping aids, especially the ones that don’t include chemical ingestion, on the flip side, this has created a tremendous awareness of mental wellbeing and mental health. This awareness has now influenced ordinary people in using online therapy/counseling and keeping themselves involved in de-stressing activities that improve their mental health.

Source: https://blog.euromonitor.com/

 

3.Immunity strengthening nutrients and supplements

Building immunity is considered as one of the crucial shields against Covid-19 and other diseases. People with better immunity levels tend to fight infections better. This concern towards building immunity has led to people trying various home remedies, wonder foods, and a lot of vitamins, minerals & supplements (VMS). 

A recent Civic Analytics Consumer Survey has shown that there is a 10% -15% surge in spends on VMS globally. These proactive self-care trends to relieve the stress during the quarantine are expected to persist well past the COVID-19 quarantine and thus, resulting in increased demand for VMS globally.

Source: https://www.lek.com/

4.Remote healthcare and telemedicine

Due to the COVID-19 situation, people are reluctant to visit the hospital to treat other ailments, especially older people who are too vulnerable to contracting the virus. At the same time, doctors and nurses who are risking their lives on the frontline are demanding new ways to treat patients. These are the kind of scenarios where remote healthcare/telemedicine come to the rescue. 

Through advancement in technologies for remote diagnostics, remote testing, and platforms that securely store patient’s information, a pandemic like COVID-19 has triggered a large scale acceptance among ordinary people. Telemedicine combined with online pharmacies has revolutionized how people approach medical diagnostics and treatment.

 

5.Growth in the usage of wearable devices

A wearable is a category of electronic devices that can be worn as accessories or embedded in clothing. The generic wearables available today are smartwatches and fitness trackers that help measure and monitor physical movements and vital health metrics such as temperature and heart rate. 

The COVID-19 outbreak that has led to that has increased sales of smart wearables from USD 2 billion in 2019 to USD 16.12 billion in 2020 at a compound annual growth rate (CAGR) of 22.37%. The need for monitoring the health vitals to track and identify illness is the main factor that fuelled the surge in smart wearables sales.

source: https://www.mekkographics.com/wearables-market-growth/

The brands which are able to stay up to date with these changing trends tend to garner greater market share and can increase their growth exponentially. The major differentiating factor always boils down to superior consumer insights.

SetuServ’s VOCIS platform would help you and your organization with the latest market insights and trends which are actionable and benchmarked against competition to leverage on points of parity and differentiation to stay ahead.

Gone are the days where marketers were shooting in the dark with their campaigns and hoping for success. And, gone are the days where marketers solely rely on inefficient survey data to understand their target audience and their competitors. In today’s scenario, technologies such as Artificial intelligence (AI) and Machine Learning (ML) are at the forefront of every innovation. These technologies predominantly help in the transformation of an enormous volume of data into insights that allows better decision making. Before going further, it is essential to have an overview of AI and ML.

Source: https://sloanreview.mit.edu/wp-content/uploads/2019/02/GEN-Kardon-AI-B2B-Marketing-1200x627-1200x627.jpg

What is Artificial Intelligence?

Artificial intelligence is the science and engineering of making computers behave in ways that, until recently, we thought required human intelligence. 

What is Machine Learning?

Machine Learning is a subset of AI, which enables machines to learn from past data or experiences without being explicitly programmed.

 The following Infographics by Smart Insights, the creators of the RACE Planning Framework, outlines the various possible applications of AI & ML across the customer lifecycle.

The following are the five areas in which the AI & ML technologies are extensively and actively being used in e-commerce improving marketing and business outcomes.

Generating Customer and Competitor Insights

Collecting and analyzing customer data from various sources allows us to discover insights that help in precisely recommending relevant products or services, thus increasing sales and customer experience. Text-mining customer reviews from e-commerce sites, social media, blogs, and review websites, and applying sentiment analysis algorithms provide a precise perception in which the customers view the products/services. These valuable insights help e-commerce companies in product optimization and filling customer experience gaps. Additionally, this analysis also assists in unearthing upcoming market trends and helps in staying ahead of the competitors.

Customer Segmentation

Customer segmentation is the method of grouping customers of similar characteristics, and it’s one of the cornerstones of effective marketing. Segmentation traditionally was done on the basis of age, gender, and other demographic parameters only. Though this helped marketers in dividing the customers into larger generic groups, it failed to help them understand the customers deeply. Implementing AI/ML in customer segmentation removes these limitations by leveraging customer behavioral data in creating more targeted segments that improve the efficiency of the marketing initiatives. Utilizing AI/ML in segmentation is not only efficient and scalable but also removes the human bias that’s involved in the traditional process.

Source: https://thefinancialbrand.com/wp-content/uploads/2019/10/micro-segmentation-flow.jpgngs/2019/02/GEN-Kardon-AI-B2B-Marketing-1200x627-1200x627.jpg

Automated Content Generation

One of the factors that determine the success of the marketing campaign is the content that’s creative, appropriate, and importantly must resonate with the target audience. Yet another challenge in creating compelling content is understanding of the subject matter and industry dynamics. Marketers shall leverage Natural Language Generation and AI technology in overcoming these challenges. AI has evolved to perform keyword research autonomously and deliver content that aligns with the campaign objectives. NLG used along with Natural Language Processing (NLP), enables automated response to reviews and customer queries in e-commerce and social media platforms, thus saving on the resource cause and improving customer engagement.

Source: http://ceur-ws.org/Vol-2196/BPM_2018_paper_21.pdf

Campaign Optimization

Reaching out to the right customers with the right content at the right time defines the success of the campaign. Nevertheless, customers also demand hyper-personalized communications and offers that resonate with them. As a result, it has become a mounting challenge for marketers to adjust and optimize their content in real-time. Taking advantage of AI-powered analytical optimization helps marketers meaningfully utilize every penny of the marketing budget in acquiring customers. The AI algorithms are capable of accessing the market, competitors’ SOV and layers the same with campaign objectives in intelligently placing the Ads for better CTR and conversion.

Demand Forecasting

Demand forecasting prevents e-commerce companies from having an excessive amount of goods in stock or out-of-stock. It uses predictive analytics, a statistical technique used in Machine Learning, to precisely forecast customer demand by analyzing historical data. These forecasting insights help e-commerce companies reduce supply chain costs and optimize financial planning, capacity planning, and risk assessment decisions. Marketers shall leverage demand forecasting by incentivizing customers with offers to buy products/services during a low demand period and plan resources during high demand to sustain customer experience. One of the common pitfalls is that it would be hard to predict the demand accurately for new products. However, using data from products of similar categories helps to overcome this challenge.

Source: https://d3e3a9wpte0df0.cloudfront.net/wp-content/uploads/2019/11/Fashion-retailers-image-11.jpg

 

SetuServ’s VOCIS platform employs a state of art AI and ML algorithms specifically modelled for the e-commerce industry that enables text mining from various sources and helps in delivering insights and content recommendations leading to business development.

The Key Advantages Of Mining Customer Reviews

 Technology is breaking down the entry barriers for new brands especially in terms of distribution and marketing, aided by factors such as smartphone usage and internet penetration. Subsequently, the evolution of e-commerce has resulted in extreme disruption of the retail industry over the past decade. In a short span, E-commerce went from being the disruptor channel to the only available option for many product categories, due to its increased adoption. In fact, recent research from Grand View Research estimates the current E-commerce global market to be USD 9.09 trillion and expected to grow by a CAGR of 14.7% from 2020 to 2027. 

The indisputable fact is that superior customer experience are the critical factors that helped sustain this tremendous growth. With mobile, internet, and other technological advances ensuring ease of purchase, both the e-commerce companies and the sellers have started focusing extensively on improving the customer experience to keep their business afloat and stay ahead of their competitors. And, customer reviews are invaluable in providing meaningful insights. In addition, customer reviews greatly impact purchase decisions, as 97% of the online customers read reviews before buying a product online. The following are the three richest public data sources for mining and analyzing customer reviews for business growth. Together, these sources can 

1. Identify influential factors to product satisfaction
2. Isolate customer experience pain points 
3. Track consumer response to competition.

Mining Customer Reviews

Before identifying the source to mine the customer reviews, it’s essential to narrow down which customer review channel works best for the objective of the analysis. The raw customer reviews data can be extracted from the following sources individually or as a combination of sources based on the business goals.

E-commerce sites:

Most of the e-commerce platforms, including famous ones such as Amazon, eBay & Flipkart, enable and encourage their customers to rate and post a review on the products that they have purchased. This source is the most reliable customer review data that’s mined online.

Social Media:

In recent years, many customers have started expressing their opinions about products and services on social media. It has also become a channel where brands are actively engaging with their customers, making it an emerging channel in mining customer reviews.

Review websites and Online Forums: 

Review sites, niche blogs, and online forums can be excellent sources of reviews of a particular product segment. At times, many customers prefer voicing their concerns on review sites and forums, rather than posting on social media.

The raw textual data are mined from the above sources using distributed crawling techniques and pre-processed by using Stop words Removal and Normalization techniques before using Natural Language Processing (NLP), Machine Learning, and Sentiment Analysis Algorithms to extract meaningful insights.

 

Advantages Of Customer Review Mining

The insights derived by mining customer reviews assist the business growth and in improving the customer experience with the following aspects.

Identify Influential Factors:

Customer Review insights would help in understanding the factors, features, and attributes influencing the buying decision and that the customers really care. These insights assist the business in better product placement among the target segment, thus leading to better business outcomes.

Optimize Customer Experience 

The customer reviews not only help us understand the sentiment of customers towards the product and services but also helps in understanding the underlying product issues and service gaps leading to those sentiments. Improving these shortfalls helps in sales growth and in generating additional positive reviews.

Track Competition

It’s quite usual for the customers to compare the product with its competitor in the same segment while posting reviews. Analysis of these reviews would provide the precise shortfall of the product or service respective to its close competitors. This analysis also helps in understanding the dynamics of the market segment, thus contributing to valuable insights holistically on the ecosystem for better decision making.

 

SetuServ’s Voice of Consumer Insights and Signals (VOCIS) platform is capable of tracking millions of data points from multiple sources, and analyzing the same using AI models with custom taxonomies based on the market segment. This analysis helps businesses in precisely understanding the market landscape and purchase drivers influencing customer decisions.

People’s lives across the globe have been disrupted and impacted in unprecedented ways due to the current COVID-19 pandemic situation. The spread of this pandemic has meddled with the lives, livelihoods, communities, and businesses worldwide. The Asian Development Bank (ADB) has forecasted that the COVID-19 induced economic loss could go up to $8.8 Trillion, i.e., 9.7% of global GDP. The International Labour Organization (ILO) has pointed out that more than 400 million full-time jobs have been wiped out globally due to this pandemic.

Source: https://medium.com/@TheDataArtist/creating-wordcloud-from-twitter-feed-using-r-370f509275af

This pandemic has also brought in a unique set of social and economic challenges that have emphasized the actual value of identifying a business’s strengths and weaknesses, as well as recognizing and mitigating associated risks. At this critical juncture, organizations around the world have pushed themselves in innovating solutions to limit the economic disruptions and put them back in the path of recovery. In order to do that, it’s critical for the organizations to empathize with their customers at the emotional level. In this post, we shall discuss the importance and ways of understanding customer emotions during these times.

 

Importance Understanding Customer Emotions

With most of the customers restricted within their homes due to the COVID-19 lockdown, delivering experiences and services that meet their new needs with empathy and care would be the influencing factor in the survival of the business during this pandemic. The companies that are capable of delivering the same would create a long-lasting positive customer experience thus leading to better customer retention and sales. 

Currently, the key challenge for marketers is to get a pulse on the customer preferences in real-time and rapidly innovate to optimize the product and identify the customer journeys of the target segment. In order to achieve the same, along with agility and responsiveness, organizations must also ensure that their decisions are backed through data and real-time research.

 

Ways to Understand Customer Emotions

The traditional marketing channels have gone obsolete during this pandemic, and the marketers have had to rely solely on  digital channels for  insights to influence their target audience. The following are the sources that can be leveraged to efficiently understand the customer’s emotions.

 

1.     Search Queries

Google, the leading search engine that processes around 70,000 searches every second and 5.8 billion searches every day. All these searches are customers trying to find solutions for their problems. That is a lot of data that can be leveraged in driving business results. A systematic keyword research shall help in understanding the following.

• Who is your Target Audience
• What are their Areas of Interest
• What are their Needs
• What is their state of mind

 

Analyzing the search queries provides insights on the customer’s emotions and needs and adds more value to the business.

 

2.     Social Sentiment

Social media has become a prominent digital platform where customers voice  both their concerns and satisfaction about the product or service. Text mining the social media posts of the target audience and performing sentiment analysis on the same  provides valuable insights about their current emotions. These relevant insights help in identifying product/service gaps and anticipated features that can be funneled to improve the customer experience leading to better business growth.

 

Setuserv’s Customer Review Insights and Signal (CRIS) platform can help businesses in improving their marketing content reflecting customer’s emotions and needs based on the automated search query analysis, and also perform sentiment analysis that helps in a deep understanding of their customers and market ecosystem. Read more about the CRIS platform here.

Technology is radically transforming the customer journey, making customers more connected and more empowered than ever before. With more than 59% of the world’s population connected via the Internet, customers are now actively voicing out their opinions on social media and other online platforms, leading to an enormous volume of user-generated content. For brands, these immense data provide deep insights into consumer behavioral trends and help companies learn about customer perceptions of their products, services, or events. Here is precisely where techniques such as Sentiment Analysis plays a pivotal role in Market Research.

What is Sentiment Analysis?

Sentiment analysis refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.

In a nutshell, Sentiment Analysis is a text analysis technique that enables interpretation and classification of human emotion and intent within the text data.

Source: https://theprauthority.com/

Need For Sentiment Analysis

Most of the Market Research focuses on quantitative metrics such as market share, market penetration, and SOV. However, there is a gap in performing qualitative analysis that helps in understanding the real pulse of the customers. The real challenge causing this gap is most of the customer-generated data such as social media posts, chat conversations, blog posts, and emails are unstructured data. This type of data is not only hard to analyze and understand but also time and resource consuming.

Sentiment Analysis employs text mining and Natural Language Processing algorithms that analyze unstructured data and derives insights that help businesses in deeply understanding their customers and competitors.

Sentiment Analysis Methodology

Below is the process flow of a generic Sentiment Analysis process

1.     Data collection

As the Sentiment Analysis leverages vast user-generated content, the raw data from various data sources such as Social Media, Blogs, Discussion Boards, Review Sites, and E-Commerce are collected and stored in a Data Lake. At this point, the data is highly disorganized and unstructured.

2.     Text preparation

This phase involves the cleaning of the extracted data and prepares it for further analysis. For efficient analysis, irrelevant information such as noise, non-contextual content, metadata, and stop words gets identified and removed.

3.     Sentiment Detection

Before leading to the next phase, it’s essential to filter the data further for efficient analysis. In this process, all the textual sentences in the dataset get tested for subjectivity. Only the sentences with subjective expressions are retained in the data set for further analysis, whereas the rest are discarded.

4.     Sentiment Classification

In this phase, the subjective text data gets classified into various sentiment classifications. After sentiment classification, the polarity of the sentiment is detected and determined whether the text expresses positive, negative, or neutral emotion. Broadly, there are three types of sentiment classification algorithms.

• ML-Based: This method uses Machine Learning algorithms, which leverages prediction models extensively trained using pre-existing labelled data.
• Lexicon-Based: This approach uses a dictionary of words in which each word gets mapped with its emotional polarity and sentiment strength. Then, the dictionary is matched with the data to calculate the overall polarity score.
• Hybrid: This method leverages the best of both above. It uses Lexicon-Based algorithms for training the prediction model, where Lexicon is proven to be more efficient. The same prediction models are used to analyze the data using ML for a quicker turnaround.

5. Analysis Presentation

Conventionally, the analysis insights were published as standalone reports and graphs. But with the growth in technology to process a large amount of data in real-time, interactive dashboards with detailed data visualization features are currently used.

Application of Sentiment Analysis in Market Research

Sentiment Analysis not only helps businesses monitor their customers’ perception of their brand but also provides valuable market intelligence on the complete ecosystem. The following are some of the secondary market research use cases of Sentiment Analysis.

•       Competitor Analysis 

Sentiment Analysis not only provides insights about your online reputation but also allows for an understanding of what customers in the target segment think of your competitors. These deep insights help in bridging the gaps in products and services to resonate with the target audience and also aid businesses in staying ahead of the competition.

•       Product Optimization

With the development of deep-dive analysis algorithms, it is possible to understand not only the sentiment of the customers towards a product but also the factors, features, and attributes.. Such insights help businesses optimize their offerings and make it attractive to their target segment.

•       Brand Monitoring

Brand monitoring is one of the most common applications of Sentiment Analysis. It helps in assessing how a brand, product, or organization is perceived by the public, especially in target segments.

•       Customer Experience

An immense amount of customer data such as chat transcripts, voice recordings, and e-mails get generated while customers interact with customer support. Measuring the customers’ reactions in these interactions would give us a clear picture of their level of satisfaction, and also reflects the performance of the support teams.

SetuServ’s VOCIS platform can help businesses perform efficient Sentiment Analysis that helps in a deep understanding of their customers, marker ecosystem, and help stay ahead of the competition. 

Share of Voice (SOV) is a critical metric in evaluating the overall marketing efforts as it reflects both marketing efficiency and product performance. In order to efficiently gauge brand visibility, it is vital to understand this metric and leverage the same to gain an edge over your competitors.

What is Share of Voice?

SOV is a brand’s share of the total spending for the category for a specific time period. In short, it’s the measure of the market the brand owns compared with its competitor. The below is the generic share of voice formula

Though there is a relationship between both metrics, SOV is often confused with Share of Market (SOM). To clarify, SOM is the brand’s share in the total sales in that category in a given time period, whereas SOV is the brand’s share of resonance in that category in the same period.

 

Why is Share of Voice Important for the business?

SOV has always been an important metric for marketers as it helps them in assessing the visibility of their brand in the marketing place. Traditionally, SOV echoed the voice of the brands and their ability to gain media exposure. But, with the increase in social media penetration and customers sharing their viewpoints on it, SOV has become the voice of the customers that brands must perceive.

 The following are the reasons why SOV is critical to the brand & business:

 Acts as a barometer to the reputation and visibility of a brand

• Measures the success of the marketing campaigns
• Helps in strategizing and optimizing marketing spends
• Helps in understanding the market and the competitor landscape
• Provides insights into the customers, competitors, industry trends and issues

How to increase Share of Voice?

If the  objective is to improve the performance and market share of your brand, it is essential to scale up the SOV.

1.   Know Your Share of Voice

The first step forward is to accurately determine the SOV, not only at the brand level but also on the Segment, Category, and Product levels. As it may sound simple, it requires a robust tool with lexical text analysis and Machine Learning algorithms that mines the following data from Social Media, Search Engines, Competitor, Review, and E-Commerce websites and transforms into meaningful insights.

 

• Brand Mentions
• Hashtags
• E-Commerce Listings
• Customer Reviews
• Ad Impressions
• Search Results

Accurate SOV not only helps to understand the brand’s position in the market landscape but also assists in better understanding the competitors and device further strategies in winning the market.

2.   Leverage Allied Metrics

SOV used in conjunction with Brand Development Index (BDI) and Category Development Index (CDI) can help marketers focus on markets that have potential and optimize their marketing spends. Growth in both BDI and CDI eventually contributes to an increase in SOV.

 

The Brand Development Index (BDI) quantifies how well a brand performs in a market, compared with its average performance among all markets. That is, it measures the relative sales strength of a brand within a specific market [Source: Wikipedia]

 The Category Development Index (CDI) measures the sales performance of a category of goods or services in a specific group, compared with its average performance among all consumers. By definition, CDI measures the sales strength of a particular product category within a specific market. [Source: Wikipedia]

Source: https://braindispenser.wordpress.com/2011/02/20/how-to-use-bdi-and-cdi-for-planning-updated/

Go With The Trend

It’s pivotal for a brand to keep up with the ever changing social trends. The best way to stay afloat as a brand is by understanding the content that’s consumed by the Target Audience. By tracking the flash trends in the market and by creating content with trending keywords and phrases shall contribute to brand awareness, thus boosting the SOV.

Influencer Marketing

Partnering with the right influencer in the niche can help to build trust in the brand. Influencers also help in creating compelling content that connects well with the Target Audience and boosts brand awareness. Knowing your influencers and the right way to connect with them and their followers is key in boosting SOV.

  

The Market Landscape module of the Setuserv’s Customer Review Insights and Signal (CRIS) platform can help brands understand their effective SOV and industry trends and help them boost their market share and stay ahead of their competition. Read more about the CRIS platform here.