We all know that consumers are irrational beings when it comes to shopping. Hence as a brand owner if you can trigger the right emotion among your consumers there is a much higher chance of boosting your businesses’ revenue.
Therefore the ultimate key to business growth in modern times is to buy CRM and thereafter scan customers’ reactions towards your offerings and adjust them accordingly for consistent sales and revenue growth.
Now when you send a well-experienced sales rep to close a deal, they, in general, know what to do based on their experience.
However, the question that remains to be answered is how you can replicate the same in online sales? Or how can you boost your brand’s customer service just by automatically scanning reviews and emails or by judging the time your web-audiences and leads spent on your web-pages or by their mouse movements?
Initiate Sentiment Analysis
To a layman, sentimental analysis can be illustrated as an umbrella term that is used for a set of algorithms that tries hard to make sense of the user’s brand perception based on the words, phrases, and punctuations they use, and also many other parameters such as the use of emojis.
At its basic form, sentimental analysis classifies a reaction of a person as positive, neutral or negative. However, recent advancements in this technology specify and categorizes reactions in a more specific way, like identifying complex emotions like curiosity, anger, happiness, depression, stress and so on.
This is possible by mining and scanning through billions of social media posts and product reviews that aids in building a dictionary based on the context used by individual words. Therefore for sentiment analysis of the customers, it is most essential to use data sets that are very much alike to the customer’s expected inputs in terms of both the language and medium or channel used for those verbiages.
It Is More Than Just Sentiments
Now although it is easy to understand now why sentiment analysis is an awesome tool for marketers, nevertheless it is not enough powerful on its own. Since, to be really efficient, sentiment analysis technology needs to be integrated with NLP (Natural Language Processing) to find recurrent themes in the customers’ feedbacks.
For example, if you are running a hotel and you get negative reviews, it is most critical to understand the exact reason that caused them like poor Wi-Fi, messy rooms, lack of parking space, unhygienic food and more.
This is because since people use several types of languages to convey the same idea, the original challenge is to classify all these variations correctly.
For example, the use of sarcasm can easily pose to be a linguistic issue for machine-based analysis. This is because even positive words can be at times misleading when it has one or more negative connotations in the same phrase, like the typical British phrase “bloody excellent” and many more.
Moreover, polite words can also be challenging to interpret using NLP as they can hide a negative impression masked inside a neutral word.
For example, the phrase “not bad” must be treated in the context of somewhat positive, even though both these words convey negative feelings.
Sentiment Analysis: Use Cases
Actually, sentiment analysis is all about reading your customer’s minds and finding out those actions that can change their moods for actions that include product launches, promotions, price variations, social projects and more.
Therefore here are a few practical and pragmatic ways that you can use this cutting-edge tool to work for your business:
If you are aware of what lead management is in easy to use CRM software you must have heard of this term as the fastest way to fail in any business is to remain oblivious to market segmentation.
This is because you must not address everyone in order to succeed but focus all your marketing efforts on individuals, companies or groups who are capable of naturally embracing and advocating your offerings.
Hence using sentiment analysis you can easily determine who these peoples are and what these things are which makes them remain happy about your business.
When gearing up for marketing a redesign or start an innovative product launch or, you can use sentiment analysis to read through the social media pages of your competitors to see what draws people to their offerings. And when you go through a redesign, you can even use this tool to make sure how your audience comprehends the new identity and adjust your communication to meet expectations.
Now once you get the results you can use your lead management software like easy to use CRM to filter these results by demography and thereafter define user categories.
Additionally, you can even borrow a concept from user experience with your brand and define user personas based on the results of your findings.
This is because by correlating the attitudes and words used by your customers with the spending habits you can set up your marketing efforts, lead nurturing techniques, or filter your sales cadence endeavors accordingly.
The meteoric rise of social media brought into our attention even new jobs like influencers and brand ambassadors nowadays.
Now, while there are several brands that choose prominent global celebrities and stars for these roles, you must not neglect the micro-influencers in the social media platforms that have small but extremely loyal communities around them and can be found by using sentiment analysis techniques.
Sentiment analysis can also be of use for finding perpetual detractors who are relentlessly talking negatively about your company.
Since once you can identify these detractors you can either block them, take legal measures or contact them directly to offer an explanation if necessary to protect your brand.
You can even use sentiment analysis as your brand evolves to find real-time feedback(s) from your customers as well as to measure and evaluate long-term relationships.
Sentiment analysis can be also a helpful method to gauge the success of your brand awareness campaigns, to track subtle shifts of the position of your brand in the marketplace or measure the effectiveness of your crisis management practices.
This is because until now machines and cutting-edge software technologies have been mostly filtering reactions based on written texts, however the stellar growth and advancements in AI (Artificial Intelligence) will bring in more ways to do this based on images, emojis and voice recordings of the consumers, which will result in producing a far more accurate result, since meta-verbal and non-verbal languages can eliminate some of the uncertainties regarding sarcasm and double-meaning words used by customers while posting on social media or while publishing reviews.