P L E A S E  W A I T...

How to capitalize on customer reviews

The rationale behind measuring your customer satisfaction

In the customer-centric world, cultivating a steady stream of positive customer reviews is a safe way to set your business apart from competitors. It is important and imperative for you to be proactive about the preferences of your customers and try to listen to them. Such an effort would help you understand your customer’s future needs and cater to it in a cost-effective way creating a win-win scenario.

There is a commonly known fact in the industry that, retaining an existing customer involves lower marketing dollars and time than acquiring a new customer. Healthy customers relationship leads to loyalty and they are more likely to recommend your products or services through word of mouth, social recommendations, online reviews, and thereby, act as brand advocates in front of their friends and family members. Many companies even gain an edge by incentivizing these customers for leaving a positive review after service or orders have been completed.

According to Searchengineland.com, 72% of consumers trust online reviews, and most of them rely on positive reviews to make online purchase decisions. But still, it is one of the overlooked aspects of customer service. Still, many managers don’t understand is that customers are often willing to give feedback to brands they have done business with and some are eager to do so! And companies end up missing out on a chance to understand what their customers want.

Why customer feedback is important

Customer feedback is a process of obtaining feedback after serving customers. It is first-hand information about your brand from actual users. Apart from identifying pain points that your customers are having with your brand; customer feedback can also be a source of innovation for ideas to improve customer service. Furthermore, customers like leaving feedback because they like feeling engaged and involved with changes at the company. Collecting and acting on customer feedback is a great way to improve your conversation rate and business success.

Customer feedback helps you to make informed decisions about your product or service. It also helps you to measure customer satisfaction among your current customers. Getting inputs on how customers view your product, support, and the company is invaluable.

How can customer satisfaction be measured?

Surveys and reviews are the most cost-effective ways to receive direct and unbiased feedback from customers. Monitoring the reviews or survey feedbacks from the customers and prospects not only helps the brand to understand the perception of their target audience but also create actionable opportunities for the Online Marketers, Online Merchandisers, Call-Centre and Warehouse Managers to improvise their Order Cancellation Rate, Merchandise Return Rate, Call-Centre Operational Cost, Marketing Cost-per-Acquisition and Margins at the Category and Product-Level.

The quantitative data from your web analytics or in-house reporting solutions can provide a health scorecard for the business and generate opportunities for optimization on the website but, it doesn’t provide any insights into what challenges individual customer segments are facing, and how can we proactively avoid those challenges at the operational level. To gain deep-dive insights into operational challenges faced by the prospective customers during their interaction with the online storefront or, during offline interaction with the call-centre reps or, their buying experience; it requires the mining of qualitative data generated via Survey Platforms and Reviews and Rating Solutions.

Reviews and Survey feedbacks can be quantitative (ratings, scores, etc.) or qualitative. While the quantitative data can be analysed easily, the qualitative data involves the much complex task of summarizing the verbatim. The text needs to be churned using appropriate text mining techniques to understand the context of the reviews and the expressed sentiment.

For one of our prestigious client, the quantitative survey data related to a client’s website showed a negative trend, but when we combined the outcome of our text mining exercise of their qualitative survey data, we learned that the visitors were disappointed as they could not locate a particular store using the store locator feature on the website. The issue was immediately fixed based on this insight and generated an additional 15% footfalls in the local branded store. So, in nutshell, Monitoring reviews or feedbacks on regular basis can help the brand to bridge the gap between user expectations and brand’s offerings.

The power of Text Mining with a real-life case study

Nabler’s Predictive Analytics Consulting team was approached by a large multi-channel e-commerce retailer based out of the United States to categorize the reviews submitted by their customers on the website into various pre-defined parameters. Based on this categorization, the Client wanted to share a list of priority actionable items with their Merchandising, Call-Centre, and Warehouse teams, which helps them to improve the quality, durability, and fit of their merchandise, reduce the abandonment rate during the checkout process, reduce the % of calls in the call-centre, and deliver a memorable shopping experience to their customers during Pre and Post Fulfillment.

Nabler team implemented the technique of training a text mining algorithm using a sample review dataset shared by the client. The algorithm later categorized the textual data based on parameters and sentiments based on the previous machine learning knowledge. The reviews were categorized into parameters relevant to the business such as delivery, customer service, quality, and cost of the product. The reviews were further categorized, to identify the sentiment related to each of the pre-defined parameters. For example, A product review can be categorized as positive for the price while negative in terms of delivery. This helps the brand retain the cost of the product while addressing the delivery related issue.

Conclusion

Based on our Text Mining exercise of their Qualitative Reviews data:

  • We were able to reduce the Quality and Durability issues for the top revenue generating product categories by more than 85%.
  • All those product categories, which were generating decent traffic but poor conversion due to pricing and delivery issues, we were able to improve the category level conversion by 20-25%
  • The % of calls to the Call-Centre for Delivery and Quality Issues were dropped by more than 65%.
  • The Order Cancellation Rate got improved by more than 25%, and Merchandise Return rate was improved by 35%.

Drive better results by understanding customer data