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Coca-Cola taps into the power of product reviews and online ratings with Harmoni

Written by Infotools | 11 Nov 2021

Infotools’ cloud-based Harmoni platform allows Coca-Cola to access and analyze social listening data at a massive scale.

 

Background

Large consumer brands like Coca-Cola understand the power of social media data and product reviews when it comes to company decision-making. In fact, data shows that around 9 out of 10 consumers rely on digital information while shopping, and two-thirds rely on reviews as their number one purchase influencer.

The Coca-Cola Company North America’s Technical Consumer Research group (TCR) is continuously scraping reviews and online ratings for an in-depth understanding of consumer opinions. These sources can prove to be extremely messy, fragmented sources of data. From the same reviews left on multiple domains, to proper coding and sentiment analysis of numerous topics, or tagging multiple themes to the same review, making sense of these is more than just downloading them from the internet.

Coca-Cola’s TCR team gathers product reviews from major online retail sources (e.g., Amazon.com, Walmart.com, etc.) and sorts these into meaningful topics.

 

The Challenge

Coca-Cola’s TCR group faced two significant challenges in sorting through the gathered data:

1. Limited processing power. Their current reporting platform was limited to 15,000 rows of data (each row representing one review), whereas TCR had already amassed over 135,000 rows of data.

2. Burdening Manual processes. TCR team members were manually coding themes and keywords into their own files to try to make sense of this information for their business.

 

The Solution

Coca-Cola’s TCR team turned to Infotools to help them bring this rich data to life in an easy and cost-effective way. Infotools has been working with Coca-Cola North America for over 20 years as its data analysis platform partner. After an initial proof-of-concept using social listening data, it was confirmed that Infotools’ cloud-based Harmoni platform was an ideal solution for providing easy user access, analysis and reporting of product reviews. The platform is made for handling large, diverse data sets.

The text-analytics solution not only allowed Infotools to ingest the metadata and pre-coded themes, it also provided TCR with multi-level sentiment analysis and AI-powered theme development for the open text product reviews themselves.

 

“It’s already doing what we couldn’t do on our own
across 16 files and over 135,000 records of data!”

 
Pamela Mittoo, Coca-Cola TCR, within 20 minutes of using the new platform. 

 

How we tackled the project

Each review is broken into theme sentences.

• Just under 137,000 reviews revealed over 410,000 theme sentences
• An average of three theme sentences per review
• Themes can be established across an entire set of data or a range of categories/products
• Data-specific themes (applying to a subset of the data) can co-exist within the Harmoni platform

Each theme sentence is associated with a base theme and sub-theme.

• 17 base themes were identified (incl. Other and None)
• 89 sub-themes were identified

A sentiment score indicates whether the theme sentence has a positive or negative sentiment within the sub-theme.

• Values lower than -0.1 indicate a negative association, e.g. “Don’t like the taste.”
• Values greater than 0.1 indicate a positive association, e.g. “Great taste.”
• Values between -0.1 and 0.1 indicate a neutral association, e.g. “I don’t like the taste on its own, but I like it in coffee.”
• Harmoni’s DISCOVER feature, which uses advanced statistical testing, automatically brings the most interesting findings to the surface to find stories in data faster by profiling the groups that matter

 

Harmoni's heavy lifting in action

Harmoni’s multi-level capabilities allowed Coca-Cola’s TCR team to immediately investigate the relationship between data points (i.e. both the respondent/review and comment/sentence level) avoiding traditional, manual-heavy data preparation steps. The platform:

• Allows multiple themes and sentiments per person to be analyzed;
• Brings much greater depth to the utilization of this data than traditional business intelligence (BI) tools, Excel, or generic text analytics solutions; and
• Facilitates investigation of the data easily, without the need for scripting knowledge.

Harmoni was able to ingest and organize TCR’s data (consisting of data points in the hundreds of thousands) in a matter of hours. It handled the data with ease, allowing the team to efficiently investigate and interact with the data. For example, they could sort results by concept or key phrase with a single click or examine a specific point - such as source or post type—with a simple drag and drop functionality.

Harmoni streamlined the sharing of findings with stakeholders through an array of reporting options, chart types, dashboards and insights visualization options

 

Economies of scale; insights of importance.

After using Harmoni, TCR’s product review database has quickly become an integral part of its “Voice of the Consumer Exploration” protocol. Having this data easily accessible and usable allows Coca-Cola’s TCR team to make decisions based on real customer feedback and avoid time-consuming manual steps for data analysis and reporting.

In Harmoni, TCR found a solution that could:

• Quickly ingest and organize large, diverse data sets, like the kind coming from product reviews.
• Handle multi-level sentiment analysis and AI-powered theme development.
• Provide a single environment for not only handling the gargantuan data processing tasks, but also take the data all the way through to analysis, visualization, dashboards and reporting.
• Allow team members to investigate and interact with the data, by doing things like sorting results by concept or key phrase to examine a specific data point.
• Give internal researchers easy ways to share the insights and democratize the data.

By employing Harmoni, Coca-Cola Company’s North Americas Technical Consumer Research group has greater customer understanding and can add business value through product reviews data.