Big Data has transformed every industry, including the hospitality vertical, and the Internet of Things is augmenting them further. Through customer analytics, targeted segmentation, and campaigning, hotels would like to focus on delivering personalized promotions — cross- and up-selling travel services.
Our objective is to address these challenges through an open-source platform providing the data analytics capabilities needed to accelerate customer analytics and render opportunities to upsell offerings. An open-source model can help achieve such business drivers by providing the flexibility needed to track and address customer activity.
Focusing on business drivers, we have observed, from the field, the following set of pain points within the Hospitality sector when it comes to challenges faced in terms of delivering value to customers:
- Need for a reliable and stable solution for analyzing e-commerce traffic.
- Missed opportunity in personalization and customer relevance translates into less effective marketing campaigns.
- Inability to centralize management and execution of all marketing effort.
- Lack of ability to construct in-depth and connected relationships with patrons to help enhance service quality and highlight true differentiation.
- Pressing need for building a customer online behavior data mart with visitor and event-level details.
- Need for consolidation of campaigns across multiple channels and improve ability to segment customer.
- Limited visibility of customer behavior and purchase patterns to provide custom offers.
- Inability to effectively customize online content and partner offers based on knowledge of visitor behavior.
Based on these challenges, an open source platform, with the capability to scale and adapt, is most suited to deliver value along with helping hotels gain customer loyalty and increase revenue, improve marketing effectiveness, and reduce the cost of service.
Value delivery can start with a few easy wins through the enhancement of the hotel experience for customers by capturing on emotional connection and derived loyalty. Traditional enterprise architectures are limited in terms of ability to assimilate data silos and incorporate non-traditional data sources.
The architecture, below, elaborates how flexible, scalable, and cost-effective enterprise data warehousing can be when built to ingest non-traditional data sources like clickstream, web and social, location, sensors (e.g. smart hotel check-ins), and more. Subsequently, value realization becomes easier by analyzing increased loyalty assessment, revenue uptick, improved marketing and sales effectiveness and reduction in the cost of service delivery.
Additionally, an improvement in these measures will help shift the focus from single, trip-level transactions to the whole customer journey cycle and enable provisioning of personalized promotions based on geography and current state.
Further, a hotel will be able to present consistent experiences to customers across channels per their preferences and, in turn, improve targeted segmentation through predictive analytics using historical behavior and transaction data that are now made possible to capture and analyze at customer’s pace.
For instance, a Hortonworks client enables their customers to check in on mobile devices and collect an electronic key, which can then be used to access room and facilities within the property. When the customer leaves, the system automatically shuts off lights and appliances, notifies house cleaning, adjusts the thermostat, etc. When the customer returns, the hotel can re-adjust those settings to his or her preference. This allows hotels to collect information on the entire customer journey within a hotel and offer them a consistent experience throughout properties across the globe.
You can begin taking action on these initiatives today by downloading the Hortonworks Sandbox and reviewing these relevant examples within the technology: