The consumer-packaged goods (CPG) space has all along needed the integration of technology, but the COVID-19 pandemic has come along to place tremendous strains on the space. The lockdowns and other changes people had to adapt to during the pandemic made CPG companies and retailers start facing challenges in the physical environment, disruptions in their supply chains, and unusual inconstancy in demand, which call for unprecedented digital transformation.
While we will be wrong to say that the pandemic has made the CPG space focus more on data, it definitely contributed its fair share. Data has become the focal point on which businesses revolve, and any brand that does not factor in data is not ready for the competition in the marketing landscape.
With the knowledge that an estimated 463 exabytes of data will be created each day globally by 2025, it dawns on anybody that we are in for a large amount of data. And as it’s expected, a large percentage of this data will be user-generated, out of which we shall have product reviews, pain points, and customers’ feelings.
It becomes imperative that the consumer-packaged goods space must put measures in place to ensure a good customer experience.
How do you handle this large volume of data?
Definitely, it can’t be done with human labor; technology must come into play. This is where you need artificial intelligence (AI).
Making sense out of reviews from customers, understanding the context, and resolving nuances can be achieved with sentiment analysis. Sentiment analysis is the automated process for text analysis and the interpretation of the sentiments behind it.
By deploying machine learning and text analytics, you use algorithms to classify statements into positive, negative, or neutral.
Brands use the process, which is also known as opinion mining, to monitor social media and to manage large amounts of data. It enables them to gain insights into consumers’ feelings as well as how the competition is faring in the global market.
CPG brands now have the opportunity due to technological advancements of accessing large amounts of information; this can be from traditional enterprise data or consumer data. If you have to gather your data from social media, you need to appreciate the fact that the use of online platforms varies by demographics.
However, the data you gather from any of the sources still remains a strategic asset to be protected and nurtured, and you need to apply it in a manner that would effectively impact the CPG space.
When AI is deployed in conjunction with sentiment analysis, CPG brands can easily generate actionable insights from such data. Where AI and advanced analytics come to very good use is in making predictions, such as the level of demand for a new product, how a new campaign can possibly impact the brand or any emerging consumer trend.
Since the data you have is basically in an unstructured format and difficult to analyze, you need to integrate Natural Language Processing (NLP) and machine learning to get the job done. Machine learning tools can differentiate between context, sarcasm, and misapplied words.
There are a lot of techniques and complex algorithms available to you such as Linear Regression, Naive Bayes, and Support Vector Machines (SVM) for detecting user sentiments. You can use these tools and techniques to separate the reviews into positive, negative, or neutral tags.
Due to the stiff competition in the CPG space, you need to have insights in real-time, and these algorithms will help you to do so. Your product analysis becomes automated, and you easily understand the voice of the customer (VoC) by leveraging qualitative eCommerce opinion insights using AI-enhanced sentiment analysis.
With insights that identify your consumers’ needs, you can go ahead to:
- Discover what your customers like and dislike about your product.
- Have insights into your competitors’ product reviews.
- Avail yourself of real-time product insights.
The integration of AI and advanced analytics solutions has ensured that decision-making processes in the CPG space are improved, customer experience is enhanced, and the time it takes to complete tasks has been drastically reduced. Research by McKinsey reveals that AI-powered forecasting can reduce between 30 to 50% downtime in supply chain networks. The insights you gather from customers’ sentiments can lead to improved accuracy of up to a 65% reduction in lost sales as a result of inventory out-of-stock situations, with warehousing costs decrease in the range of 10 to 40%.
While AI is tremendously transforming the CPG space, it’s expected that there may be a pocket of resistance in some quarters, it’s, therefore, important that brands ensure that employees are carried along in their digital transformation decision-making processes. They need to be reassured that these applications will not negatively affect their jobs, but that it will only improve their ways of working and ultimately the customer experience.
CPG brands stand to gain from deploying select AI and advanced analytics applications, but the overview should be on how the transformation can eventually make the customer the focal point. There are large volumes of consumer-related data out there that CPG companies can access for veritable insights into the sentiments of consumers as well as tools and algorithms to comprehend these sentiments.
This will be of great help in the decision-making process from product design to supply chain, and marketing to sales. It has not always been easy to transit from a traditional way of doing things, but looking at the overall picture, the CPG space is set for a mammoth transformation that will be overwhelmingly rewarding.