By Guy
Yehiav, Profitect
Online brand and product reviews today are an important part of
the retailer-shopper relationship. As more consumers take to the Internet and
social media to share their retail experiences and feedback, retailers must be
keenly aware of how reviews impact brand reputation, risk and even their bottom
line. Given this impact, reviews serve as an interesting and informative data
point that can help retailers improve the shopper relationship, and ultimately
sales. But the question remains, how can brands leverage this information?
The answer lies with prescriptive analytics, which provide
retailers with a quick, effective way to read and interpret the data or reviews
they are collecting. Powered by machine learning and AI, prescriptive analytics
can identify areas where things are already working well or where the retailer
can improve operational efficiency. When it comes to reading and interpreting
reviews is where sentiment analysis
comes into play. Sentiment analysis combs through textual data, like reviews
and comments, isolating buzzwords and key themes that retailers value. This
could be anything from customer satisfaction or dissatisfaction to pricing,
service, cleanliness and product quality.
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While there are other solutions that can address this problem for
retailers, few of them can accurately capture true intent the way sentiment
analysis does. Understanding intent is critical to understanding the true
meaning behind a comment and getting accurate insights.
For example, consider these two fictional comments about a
handbag:
- “I bought this cheap purse.”
- “I bought this purse cheap.”
Notice that despite having
the exact same words, the order in which the words appear changes the meaning.
#1 has a negative intent, while #2 is more positive, highlighting a great deal.
Having an effective way to manage and understand reviews and their meaning
helps retailers collect accurate insights into consumers’ shopping experiences
or product issues.
A second benefit of
leveraging a sentiment analysis solution is that it provides an effective and
efficient way for retailers to act on
this type of data. Instead of compiling all of the data from reviews into
mind-numbing spreadsheets (which often take hours to digest) — or even worse,
scouring online reviews every morning — prescriptive analytics provide store
associates or brand owners with prescribed actions that are based on the data
sets collected.
For a real-world client
example, a retailer introduced a new line of warmer-weather clothes last fall
in anticipation of a cold, dreary winter season. After a few days, there was a
significant uptick in negative reviews around one of the jackets in the new
line. Consumers were complaining about how the material was not holding up well
after washing and drying, and were showcasing why other consumers should not buy the product. The prescriptive
action from sentiment across all of the reviews brought this detail to the
retailer’s attention quickly, highlighting that the jacket material needed to
be re-evaluated. This insight allowed the retailer to react quickly and add a
“Dry Clean Only” tag to the remaining product, which solved the issue and saved
sales for that particular jacket.
Prescriptive analytics and
sentiment analysis solutions are not only helping retailers save time by
combing through massive amounts of data and reviews, but also by highlighting
only the reviews that truly need addressing: price, cleanliness, satisfaction
or profiling. When you combine all the information you need — the unstructured
data, the scores and intents assigned to it by sentiment analysis, and the
corresponding KPIs (i.e. sales reports, return rates, merchandise quality, damages,
etc.) — you have everything you need in order to drive operational efficiency
and improve the customer experience.
As CEO of Profitect, Guy Yehiav is responsible for
overseeing the overall corporate strategy and direction for the company. A 25+
year retail supply chain industry veteran, Yehiav has guided the company
through multiple concurrent years of significant double-digit growth. Prior to
Profitect, Yehiav served as Vice President Sales & Strategy for Oracle’s
Value Chain Planning Solutions, where he was responsible for sales, strategy
and customer success. He also was founder of Demantra US, a leading global
provider of demand-driven planning solutions, which was acquired by Oracle in
2006. Previously, he directed the Global Professional Service Group, where he
was in charge of creating methodologies and infrastructure through value chain
transformations that enabled demand driven and seamless operations for Fortune
1000 companies.
