Big data—in its current form, at least—is dead to me, I know this is a strong statement in a world seemingly powered by the concept, but companies simply are not using big data properly, rendering it useless for driving change and increasing revenue.
By Margaret Ady of TrustYou
Case in point, back in my corporate days, researchers would present numbers without any context or action. A statement that conversions are up 6% or ratings have decreased 8% means nothing without the story—the before, the goals, the changes along the way that are influential. It’s high time we replaced big data with smart data.
Smart data that is actionable and insightful can transform the way we operate our businesses.
Let’s take review data, for instance. For hotels and most other service or product companies, reviews are essential for success.
An integral part of the search-shop-buy experience during a consumer’s path to purchase, reviews have a cascading effect on business: positive reviews bring customers and their positive reviews bring even more customers.
Negative reviews, obviously, discourage consumers from purchasing, and when problems aren’t fixed, the consumers who purchased despite some negative reviews then write more negative reviews. This cycle works wonderfully for consumers, helping them to make smarter purchasing decisions by wisdom of the crowd, but for businesses, leveraging this cycle can be tricky.
How can business owners decipher all of this review content? In the hospitality industry alone, there are more than 350 million reviews published across the web, in dozens of different languages, on hundreds of different websites.
Each one of those reviews has, on average, seven different data points about the service, room, food, and so on—also known as sentiment categories. Add it up, and there are billions of data points to understand.
Enter big data.
A plethora of big data companies offer to structure all of this information so that businesses can see average scores of reviews and scores for various sentiment categories, an incredible technical feat, I am sure. However, it is really all that useful? What does an average review score of 85 or a hotel’s room score of 62 actually mean?
Gartner Research reports that 80% of companies are struggling with using their data. This is because many executives don’t know how exactly to interpret the numbers.
Because of this, the data is often pushed aside. What businesses need are insights behind the numbers so that they can identify trends, create forecasts, improve scores, and ultimately generate more business.
Enter smart data.
Smart data, a concept that some tech companies are catching on to, provides insights from big data, allowing businesses to make actionable change within their organization. It makes the task of identifying what is and is not working simple. Two keys to smart data are: 1. understanding the ‘whys’ behind the numbers and 2. using data to prioritize changes that will have the biggest impact on the bottom line.
Understanding the ‘Whys’
Having texture behind structured scores provides businesses with enough context to make actionable change. For example, if a hotel receives a negative review score for its room, it can use tools such as TrustYou to uncover review snippets written about the room to understand why its scores are low. It transforms this finding:
3,298 reviews written this month show that your rooms have a score of 62.
3,298 reviews written this month show that your rooms have a score of 62 because they are not clean and the air conditioners don’t work properly.
Using Data to Pinpoint Where to Invest
Not every complaint deserves the same level of attention when it comes to repairs or improvements, and identifying which problem areas do deserve attention can vary from business to business. Smart data allows businesses to understand where to invest based on the factors that will have the greatest impact on their bottom line.
Take Impact Scores, a new element of TrustYou Analytics that shows hotels which complaints or praises have the greatest impact on a reviewer’s overall satisfaction using a complex mathematical model to isolate positive and negative sentiment categories.
These scores show exactly how much review scores will change with positive or negative mentions within each category. For example, an impact score of -3.3 for service means that reviews with negative mentions about service will result in a 3.3% drop in overall scores. Areas with the most negative impact scores deserve the most attention, arming hotels with a priority list of issues to address that will have the greatest impact on guest satisfaction and ultimately, bookings.
At the end of the day, big data is completely worthless if businesses don’t know how to use it to drive change. The benefits of transforming this data from big (i.e., quantity) to smart (i.e., quality and context) go far beyond improving services and the resulting improved scores.
Businesses become more efficient at handling issues when it is clear which ones matter most and why. And, when better reviews arrive, those businesses can harness them in marketing and to improve their web presence for a hefty impact on their bottom line
See original article at http://www.4hoteliers.com/features/article/9546?awsb_c=rss&awsb_k=xfeed