Page 152 - Building Big Data Applications

150 Building Big Data Applications

of delayed/canceled flights due to bad weather conditions. Their competitor, who had
used a manual system to manage disruptions, canceled 22% of flights, whereas this
company reduced the number to 3.4%. This is a real life application of big data analytics
and applications.

Niche targeting and unique selling propositions

Data science is not reserved for the big brands only. Smaller travel companies can
leverage their existing data sets to become the best within their segments, instead of
competing for every/any kind of customer.
A boutique hotel chain has properties in multiple locations. They collect customer
data from travelers and have a lot of valid information that can be leveraged to execute
several analytical algorithms that will deliver outcomes to hone their unique value
proposition. Instead of pursuing a large pool of target clients, the chain’s CDO decided to
focus on pursuing a microlevel niche demographic, travelers with a specific business-
level budget.
To execute the nearest neighbor algorithm, the hotel chain aggregates on-site data
into a central dashboard system that allows managers at all locations to review every
guest interaction, and obtain further insights on how to improve customer experience.
The company specifically focuses on attracting the one particular type of customer and
builds strong matches between customers and properties. The accumulated data is used
to make better decisions about services and craft more targeted marketing campaigns
targeting “look-alike” prospects. Small businesses in the travel industry can follow the
botique’s lead and maximize their internal data to pursue the right customer, instead of
wasting budgets on ineffective marketing to a broader segment.

“Smart” social media listening and sentiment analysis

Social media is a two-way communication alley. Sharing updates are not enough to
succeed. You have to communicate and listen to your customers and prospects.
Applying data science to social listening can help marketers consolidate large amounts
of scattered data and turn it into specific market research campaigns. Most travel
companies have accounts registered on popular networks, yet they view “social media”
as a separate entity, rather than an organic extension for their marketing business.
Travel brands can leverage social media to create highly targeted buyer personas and
scout for “look-alike” prospects. All the conversations happening around the customer
or prospect can be collected and studied, analyzed, and refined to the key points that are
being discussed. The new data can then be used in machine learning execution of
unsupervised data, where the patterns are more identified and can be leveraged to
attract potential customers.