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The Role of Big Data in Revenue Management Recovery

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Two cornerstones of sustainable revenue management are demand prediction and elasticity of pricing.

Both of which are virtually impossible without accurate data to ensure the correct pricing, at the correct time, is applied.

 Enter: Big Data. Hospitality firms are rife with data. That data is becoming more and more important to business health and revenue stream considerations. This is especially important for revenue managers, who need to have an eagle eye on customer spending trends and budgetary pressures to develop future-proof revenue strategies. Revenue managers need to know how, where and when every customer interacts and spends money in and on their business. But are the legacy systems that manage and collate information to service revenue management outcomes enough in the age of Big Data?

How exactly does Big Data help revenue management recovery in the age of COVID?

What is Big Data?

Big data is a term that describes large, hard-to-manage volumes of data – both structured and unstructured – that inundate businesses on a day-to-day basis”. Big Data generally refers to incredibly large amounts of data that is too unstructured and voluminous for humans to handle, clean, and derive meaningful information from. The advent of cloud computing has made Big Data handling and processing much more affordable and usable.

Plus, the rise in digital connectedness between business and customer, the increase in touchpoints and enormous amounts of data generated from website traffic, social media interactions and marketing engagement has further exacerbated the sheer scale of data hospitality companies need to organise to make better business decisions. SAS further highlights the importance of two distinct Big Data features that make all the difference when considering data analysis and how exactly to use data to meet revenue goals:

  • Variability of Data: “Data comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, emails, videos, audios, stock ticker data and financial transactions”.
  • Veracity of Data: “Veracity refers to the quality of data…businesses need to connect and correlate relationships, hierarchies and multiple data linkages”.

In short, successful use of Big Data comes down to ensuring good quality data is analysed, and that the right channels are open for analysis to gather said data. Considering the vast array of touchpoints involved in searching, booking and purchasing from hospitality companies, and the channels in which customers find companies, it’s no wonder Big Data is considered prime revenue generation fuel.

The limits on revenue managers when considering Big Data

“That being said, the actual development of a Big Data management platform is a costly endeavour, both in terms of financial costs and finding the people with the skills and knowledge to be able to complete a project of this scope”. Revenue management takes analysis and accuracy. That analysis needs to take stock of customer expectations and how they stand up against market expectations.

It has to seamlessly interact with data generated through a PMS, and integrate with on-site systems. This, of course, costs money. But Big Data - and the tools that organise and “clean” the data - are integral to revenue management recovery.

Why is Big Data so important?

Revenue Acrobats highlight three core reasons why Big Data is so integral to revenue management: personalisation, segmentation and forecasting.

  • Personalisation - by utilising Big Data effectively, revenue managers and operators can build more accurate, more personal customer profiles. They can adjust service offers and operations around real-time customer feedback and build more relevant, more investment-worthy experiences.
  • Segmentation - Big Data is central to creating more impactful elasticity in pricing. Consider Big Data the dynamism in dynamic pricing. You can more accurately and more appropriately set pricing to customer segments more confidently, with more data. It means market segments can offer more personalised pricing based on more relevant data, too.
  • Forecasting - anticipation of demand, and building strategies of pricing and promotion to meet expected demand, is an essential tenet of good revenue management. Through analysing Big Data, revenue managers can create order to the vast array of search, demand, trend and competitor data sets, and create a high level of forecasting reactivity and preparation using frontline historical, PMS, customer and seasonal data.

In summary, Big Data can be an enormous concept to get a business head around. Big Data provides hyper-relevant market information for operators to implement business changes to meet the demands of contemporary customers. In a pressured hospitality environment, these sorts of industry insights are the difference between growth and stagnation. Successful implementation of data analysis can garner incredible business improvement results, improved customer satisfaction and, ultimately, more revenue.

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