While gas prices continue to plummet across the nation, consumers may still find themselves driving from station to station as they search for the lowest local price per gallon. Owners understand that, based upon location and demand, they have the freedom to adjust pricing according to how much local residents are willing to pay. Though simple in its application, such behavior represents optimized pricing at its core.
Harkening back to the days of brick-and-mortar domination, pricing optimization refers to the process by which retailers and service providers align their pricing strategies to coordinate with the behavioral trends driven by their consumer base. Even today, it's common to find brick-and-mortar stores with varied pricing based upon their location and customer base. However, as digital becomes an indomitable force throughout today's retail and service ecosystem, businesses must now readjust their pricing strategies to accommodate e-commerce habits and patterns.
"When prices don't make logical business sense, it's often a significant source of customer dissatisfaction," Barrett Thompson, general manager of pricing excellence solutions at Zilliant, highlights. "Forward-thinking companies are using optimized, rational prices as a selling point with their customers and a true competitive differentiator. The result is improved financial performance and better customer satisfaction, creating a win-win for companies and their customers."
Using data analytics, companies can now optimize pricing strategies dynamically by using the consumer's browsing behavior and geo-location data to assess demand. Such tactics account for local demand, store location, and competition, allowing brands to determine the highest price customers are willing to pay. In the case of brick-and-mortar stores, companies constantly reflect upon their competitive situation so they may drive customers to their door. For instance, the only toy store in town would likely have higher prices than if it were to share the space with its big box competition. Thus, online markets can apply behavioral data in the same fashion in order to adjust pricing based on the shopper's proximity to the competition or likelihood to commit elsewhere.
"Today, consumers have greater knowledge of the purchase options available to them in the marketplace thanks to the Internet, so there's greater elasticity of demand as a result of substitution effects among competing brands," says Don Ryan, senior partner at iKnowtion. "That's the benefit consumers enjoy. On the flip side, the increase in the ability to make 'private offers' to consumers via direct marketing and online platforms means that companies can more easily price discriminate, which is an effective way for them to maximize purchase rates and revenue."
Ryan notes that, when establishing optimized pricing strategies, brands perform analytical experiments to determine how existing customers and prospects are likely to react to various prices in the given market. Companies need not invest in special technologies, for they need only collect the right data from the right consumer population to establish their strategies. From market tests to mimicking market conditions, data allows brands to construct pricing simulation tools that can then be used to evaluate expected impact. Pricing algorithms are also developed based upon recent market behaviors or experiments with the space. Such tools can be incredibly valuable in determining how to differentiate prices at the individual level, but they must be monitored constantly to assess how accurate these models are at predicting results.
"Algorithms should be calibrated to adjust for differences in predicted purchase rates," Ryan adds. "Furthermore, it should also be remembered that, in today's dynamic environment, market conditions can-and often do-change very rapidly, which might render the pricing models obsolete in a short period of time. Consequently, any solution that's aimed at optimizing pricing offers on demand should be reviewed frequently."
But, while consumers are increasingly aware of such practices, many have yet to grow comfortable with such pricing strategies, as they find them to be deceptive in nature. Shoppers that happen to come upon price discrepancies by accident typically feel duped and cheated, thereby losing trust in the given brand.
One recent study conducted by Northeastern University emphasizes that, while such practices have the capacity to be advantageous, retailers must act transparently to avoid alienating customers. Researchers examined 16 e-commerce websites-10 general retailers and 6 hotel and car rental sites-by measuring the extent to which each brand engages in two particular forms of personalization: price discrimination and price steering. Price discrimination occurs when companies customize product prices according to the given user, while price steering occurs when brands modify search results based upon customer behavior.
Overall, the study revealed that popular travel websites, such as CheapTickets and Orbitz, engage in price discrimination by offering reduced prices on hotels to registered members, while national retailers, such as Home Depot, display higher prices for consumers on mobile devices than those browsing via desktop. Thus, said results confirm that, while such practices are reminiscent of brick-and-mortar behaviors, brands must not hide behind the guise of e-commerce. Just as businesses are honest about senior discounts and student price breaks, companies must also disclose underlying pricing optimization strategies.
Don Peppers, founding partner at Peppers & Rogers Group, recalls one instance in which he was listening to incoming phone calls at a contact center for a credit card and financial services firm. One customer, "Mrs. Smith," called because she was considering switching to another company that offered reduced fees and lower interest rates. Luckily, the agent was able to offer Mrs. Smith the same deal in real time in order to prevent defection. But, when "Mr. Jones" called about the same competitive offer, the agent was unable to offer him something comparable at that time. Of course, it's obvious that Mrs. Smith received this offer because her credit history proved her to be more profitable, while Mr. Jones was clearly less reputable.
However, while this example of price discrimination may be deemed sneaky or deceptive, Peppers notes that, to maintain trustability and drive continued demand, companies must be willing to explain why one customer received an offer and the other didn't. Transparency remains at the heart of successful optimized pricing strategies, for brands must sustain trust as they seek to maximize profits. Hiding such practices will ultimately hinder reputation, triggering customer churn. Deep down, customers understand the purpose of such practices and the benefits of said strategies. Thus, brands must be open and honest, for all parties must be on the same page in order for pricing optimization to persist and evolve successfully.