In today’s digital-first world, customer reviews are not only a source of valuable feedback but also a driving force behind purchasing decisions. An estimated 90% of consumers read reviews before making a buying choice, and 72% are more likely to act if a product has positive feedback.

These stats are consistent with my experience in consumer product marketing at Amazon and other great organizations. For product marketers, this treasure trove of customer input can reveal valuable insights, yet it can also be overwhelming to analyze manually.

This is where attribute sentiment scoring comes in—a technique that leverages natural language processing (NLP) to dissect reviews based on specific product attributes, shedding light on what customers really think about each element of a product.

In this article, I explain the concept of attribute sentiment scoring, how it works, and why it has become an essential tool for product marketing.

What is attribute sentiment scoring?

Attribute sentiment scoring is a process that evaluates customer sentiment toward specific attributes of a product—such as durability, ease of use, or value for money.

Unlike a general sentiment analysis that categorizes a review as positive, neutral, or negative, attribute sentiment scoring digs deeper to analyze sentiments associated with each attribute individually.

This approach, which has been a boon to companies I’ve served such as Amazon, offers more granular insights that can directly inform product development, marketing strategies, and customer support.

For instance, while a general sentiment analysis might reveal that a product is “mostly positive,” attribute sentiment scoring can highlight that customers love its functionality but have issues with its durability.

I have found this level of insight to be crucial in my product marketing journey when I want to pinpoint strengths and address specific weaknesses in my messaging.

So you want to become a product marketing manager?

From key skills needed for career progression to how to choose your next role and more, here’s how to break into product marketing management.

Product Marketing AllianceLawrence Chapman

How does attribute sentiment scoring work?

At its core, attribute sentiment scoring relies on advanced NLP algorithms to detect keywords, phrases, and sentiment indicators in a review text. Here’s how I have seen this process typically unfold:

• Attribute identification: First, the system identifies key product attributes mentioned in reviews. For a smartphone, these might include battery life, screen quality, camera, and performance.
• Sentiment detection: Next, the algorithm assigns a sentiment score to each attribute. This is often achieved by analyzing adjectives, verbs, and modifiers around each attribute. Words like “great,” “amazing,” or “superb” might indicate positive sentiment, while terms like “poor” or “unreliable” would signal negative sentiment.
• Score aggregation and visualization: The sentiment scores are then aggregated, often on a scale of -1 to +1 (where -1 indicates strong negative sentiment, 0 is neutral, and +1 is highly positive). Visualization tools can then plot these scores for easier interpretation.
• Contextual analysis: More sophisticated models use contextual sentiment analysis to understand when certain words change meaning based on context. For example, “long” could be a positive attribute for battery life but a negative one for response time.

This process has helped me and my product marketing team gain a multidimensional view of customer sentiment that extends beyond a binary positive or negative label.

Why sentiment matters in product marketing

I strongly believe that understanding sentiment is critical for product marketers, as it directly impacts our brand perception and customer loyalty. From my experience, here’s how attribute sentiment scoring can make a difference:

1. Enhances customer understanding

By focusing on attribute-specific sentiment, marketers can identify exactly what resonates with customers and what doesn’t. This level of understanding goes beyond surface-level data, providing actionable insights to refine product messaging, inform new features, and address pain points.

For instance, if sentiment analysis shows positive feedback about ease of use but negative scores for customer support, marketers might emphasize ease of use in their campaigns while working with the customer support team to improve the experience.

Build a customer-centric culture to empower your employees

As a CS leader, there’s a responsibility to set the standard through your actions. Fundamentally, any big change needs to come from the top. To ensure each customer interaction counts and your whole company recognizes and values each customer interaction, this needs to come from the C-suite.

Product Marketing AllianceGrace Gupta

2. Informs product development

Attribute sentiment scoring enables a feedback loop between marketing and product development teams. With insights into specific attributes, product teams can address issues that matter most to customers.

For instance, if a majority of reviews reveal dissatisfaction with battery life, the product team can focus on improving that aspect in the next version.

This feedback loop is invaluable for prioritizing resources and aligning the product roadmap with customer expectations.

3. Optimizes marketing messaging

With granular insights from sentiment analysis, product marketers can refine messaging to highlight strengths and address concerns proactively.

For instance, if many reviews praise the “fast processor” of a laptop but raise issues with the “heating system,” marketers can emphasize the laptop’s processing power in promotional materials and include messaging around heat management or durability.

Messaging based on specific attributes can lead to more targeted, impactful campaigns that resonate better with prospective customers.

4. Strengthens competitive positioning

Attribute sentiment scoring can also be applied to competitor reviews, providing insights into how a product stacks up against the competition.

If competitors’ products consistently receive low sentiment scores on an attribute where your product excels, you have a competitive advantage to leverage in your marketing.

Understanding the competitive landscape at this granular level empowers product marketers to emphasize strengths in areas where rivals may fall short, creating a differentiated positioning strategy that attracts potential customers.

5 clever ways to ask for reviews from your customers

Here are five ways to request and collect customer testimonials and product reviews to reduce awkwardness and increase response rates.

Product Marketing AllianceSteve Norall

Implementing attribute sentiment scoring in your product marketing strategy

To start leveraging attribute sentiment scoring in your product marketing strategy, I would recommend the following steps:

1. Define key attributes

Work with product and customer support teams to identify the most critical product attributes from the customer’s perspective. These might include design, usability, features, and pricing, depending on the product type.

2. Choose the right tools

A variety of sentiment analysis tools are available, each with varying levels of sophistication. Platforms like MonkeyLearn, Lexalytics, and IBM Watson can analyze sentiment on a granular level. More advanced tools may offer customization options to adapt to industry-specific vocabulary.

3. Analyze and segment data

Once you’ve gathered sentiment scores, segment them by customer demographics, geography, and user type. This segmentation will provide even deeper insights, allowing you to identify trends across different customer groups.

Geographic segmentation data + how to use it

If you sold umbrellas, you’d have a better chance at marketing them in London, where it typically rains over 100 days per year, than Dubai.

Product Marketing AllianceStevie Langford

4. Translate insights into action

Share sentiment analysis findings with relevant departments and integrate insights into your marketing materials, product development cycle, and customer service protocols. Make it an ongoing process to continually refine strategies based on real-time customer feedback.

Case study: Leveraging attribute sentiment scoring for success

Let’s look at a real-world example to illustrate the value of attribute sentiment scoring in action.

A well-known e-commerce brand wanted to understand why its new line of headphones received mixed reviews despite high ratings on comfort and sound quality. By using attribute sentiment scoring, they uncovered that customers were highly critical of the product’s build quality and wireless connectivity.

Armed with this information, the product team improved these features in the next iteration. Meanwhile, the marketing team adjusted its messaging to focus on the comfort and audio fidelity of the headphones. These efforts contributed to a 20% increase in customer satisfaction and a 15% boost in sales.

This case study highlights how attribute sentiment scoring can help brands turn constructive feedback into tangible results.

Customer obsession: key strategies and how to get it right

Google Cloud’s Head of Product Marketing, Sally Revell shares five key strategies that will take your customer obsession to the next level.

Product Marketing AllianceSally Revell

The future of attribute sentiment scoring in product marketing

As machine learning and AI continue to evolve, I am positive that attribute sentiment scoring will become even more powerful and accessible. Future advancements may include real-time sentiment analysis, allowing brands to react to feedback immediately, and automated scoring that adapts to new vocabulary or emerging trends.

These innovations will enable product marketers to stay even closer to customer sentiment, driving quicker, more targeted responses that enhance customer satisfaction and loyalty.

In the not-so-distant future, sentiment analysis may even integrate with augmented reality (AR) and virtual reality (VR) experiences, providing a real-time pulse on customer reactions during virtual product demos or online shopping experiences.

Imagine being able to see attribute sentiment data overlaid on a VR product display, allowing you to gauge live customer sentiment and respond instantly.

Conclusion

Attribute sentiment scoring offers a more nuanced view of customer feedback, empowering product marketers with detailed insights that drive better decisions.

By understanding not only how customers feel but also what they feel about specific attributes, marketers can improve their product positioning, messaging, and overall strategy.

As customer reviews continue to play a critical role in purchasing decisions, embracing attribute sentiment scoring can be a game-changer for brands. It’s no longer enough to know if a customer likes or dislikes a product; knowing why can make all the difference. And that’s why sentiment truly matters.

This approach to understanding customer sentiment not only aligns with modern consumer expectations but also sets brands up for sustained success. Now is the time to harness the power of attribute sentiment scoring and let customer voices shape the future of your product marketing.