A commercial strategy platform uses data from revenue, sales and marketing to identify the correlating data trends to provide insight relevant to each discipline. However, the platform analyzes the data for each department’s needs and then displays the data in a manner relevant for each of the three teams.
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Removes department bias
A commercial strategy platform removes department bias from the process by creating more accurate insights that lead to smarter business decisions. The system analyzes the data without any self-interest and provides insights based on the overall company goals rather than the goal of a specific department.
Revenue, sales, and marketing have their own departmental goals that determine how they are evaluated. The revenue department works to meet budgeted revenue goals and have the best standing in the STR report. At the same time, marketing wants the maximum ROAS (return on ad spend), and the sales team wants to close every deal. But the goal of each team is often at odds with those of the other teams.
For example, the marketing department wants to prove high return on ad spend. As a result, they’re incentivized to spend more during a time of high bookings, such as a local festival celebration, to improve their ROI. The revenue department pushes back on marketing spend during the event because the hotel will likely fill up without high influence marketing. They want marketing to spend more during times of low demand.
A CSP provides unbiased recommendations for pricing and campaigns that benefit the overall profitability not focusing on a specific departmental goal. Instead of unknowingly working against each other and lowering profitability, revenue, sales and marketing now work together towards the same goal with insightful recommendations.
Commercial strategy platforms make recommendations by using AI analysis of the data instead of predetermined rules. By comparing the potential total value of the group with a robust displacement analysis, LodgIQ makes recommendations for group bookings, such as optimal group prices and alternate dates as well as to the hotel as a whole: segmented forecasts used by the director of sales and historical data of the property and market.
Traditional RMSs, by contrast, optimize rates and restrictions but only service the revenue department. The raw data does not help companies make decisions meaning teams must devote considerable time to analyzing and understanding the data. The data provides only limited business value with no analysis included.
Revenue management platforms also operate with rules that are often counterproductive to the ultimate goal of maximizing revenue. Rules may be competitor-based, such as “Do not price more than $10 higher than (a specific competitor).” This assumes the competitor makes smart pricing decisions. Additionally, rules may have specific floors and ceilings, such as “Don’t price higher than $X.” That strategy, however, limits revenue potential.