Understanding the intricacies and process of revenue optimization requires a glance at some real world examples. Since the concept of revenue optimization was pioneered by the airline industry, we’ll start there. I’m sure almost everyone has had the experience of sitting on an airplane and asking the person next to them how much they paid for their ticket. Rarely, if ever, would the answer be the same. The reason? Ticket prices are determined by a variety of factors, including:
- When the ticket was purchased (2 weeks in-advance, or no advance)
- The class of service (economy, business, or first-class)
- Special seat and flight accommodations
Relying on sophisticated analytics and data-driven tactics, airlines (and other data-reliant businesses) are now using revenue optimization in order to boost top-line growth.
Airlines engage heavily in revenue optimization because their costs are mostly fixed (i.e. operating costs, crew salaries, and even fuel consumption to some extent) and their key revenue driver is a full plane. This notion has led many airlines to invest in big data solutions that allow them to capitalize on advanced data techniques to gain a more complete understanding of their customer and offer value-driven solutions that align with customer expectations and demands.
Airlines can now tailor their flight offerings based on customer tendencies, preferences and perceptions. Examples include discounts for early bookings, auctioning off empty seats, bundled promotions, and even allowing customers to upgrade to another class of services (that would otherwise go unused) so that they can maximize revenue on any given flight.
I recently wrote a blog post titled “Put Your Big Data to Work” and referenced a SaaS company we’re working with that is using Big Data Analytics to optimize customer SLAs. I wanted to take a quick peek into how this global HR firm is leveraging Big Data Analytics to support their revenue optimization efforts and how other SaaS-based firms can capitalize on Big Data Analytics to drive revenue optimization.
If you’ll recall from my previous post, this company developed a comprehensive suite of SaaS-based HR tools. As part of this suite, they offer multiple tiers of service levels to their customers (Silver, Gold, & Platinum) which are each based on different SLA delivery metrics (2, 4, or 6 seconds for example). Not surprisingly, this company’s SaaS product and corresponding application infrastructure represents a considerable capital investment. As a result, in order to recoup costs associated with their expensive application environment, they – not unlike the airlines we discussed above – need to engage in revenue optimization to derive maximum value (i.e. revenue) from their investment (servers, physical network, storage, maintenance, overhead, etc.)
Relying on OpTier’s Big Data Analytics platform, this company is seeking to optimize the distribution of customers on their various SLA tiers to drive additional revenue — all without incurring additional costs. To optimize revenue generated from their “stack,” the company is going to leverage advanced data analytics and contextual big data — provided by OpTier’s industry leading APM platform will be able – to:
- Optimize product availability and price to drive revenue
- Anticipate customers’ perception of value and extract the maximum amount
- Sell the right product and the right price at the right time
- Predict – to some extent – customer behavior and cater offerings accordingly
How would this look in action you ask? Well, this company would examine the SLAs of their current customers and attempt to incentive customer to upgrade tiers (while maintaining current SLAs) using relevant, timely and customized offers. Alternatively, if they have to spin up a new stack, they may be able to offer personalized discounts to customers to manage demand for the new stack and reduce costs accordingly.
For example, in the screenshot above you can see that the 20+ customers in the SILVER segment are consuming 4000+ transactions – almost ALL within SLA. We could optimize the utilization of our “GOLD” and/or “PLATINUM” technology stacks (thereby increasing revenue) by offering a “SPECIAL UPGRADE” to 1 or 2 SILVER members – UP to the “GOLD” level.
By capturing and exploiting contextual big data, this global HR can now fundamentally understand customers’ perception of product value and accurately align price/placement/availability for each segment to drive revenue. Capitalizing on OpTier’s Big Data Analytics platform, they can effectively engage in revenue optimization and drive a significant return on their investment.
To learn more about OpTier’s Big Data Analytics solutions, check out our Big Data Solutions Brief or Contact Us.
