Using Online Analytics to Optimize the Most Important Part of Your Marketing Mix: Price — Q&A with CalmSea VP of Products, Vivek Subramanian
Vivek Subramanian recently left Oracle, where he led product management efforts for Siebel Marketing and Analytics, to join CalmSea, a startup focused on helping online retailers conduct near real-time optimization of critical merchandising functions such as pricing, markdowns, assortment, promotions and inventory. CalmSea is a member of the Omniture Developer Connection community, and is currently working to integrate its science-based predictive merchandising solution with transaction data from Omniture’s Genesis APIs. The joint solution promises to offer online retailers a powerful new analytics-based tool designed to help ensure that they always have the right mix of products at the right price available to customers.
Q: In the online marketing industry we hear a lot about strategic issues related to 3 of the 4 P’s; Product, Promotion, and Placement, but rarely ever do we hear about the most important of the 4 — Price! We all learned in Econ 101 that price is a critical determinant of demand-why do you think online marketers often ignore it?
A: Great question to start off! Online retailers, with a few exceptions, have traditionally been price followers rather than price setters. Pricing has not been a strategic action but a tactical one instead with reactions to competition being the primary driver. This has led to price wars that have eaten into gross margins. One of the key reasons for this is the lack of affordable tools that can help make pricing decisions by looking not only at competitive data but also marketing, customer, inventory and supply chain data and do all this in near real-time. For example, while pricing a product you need to consider past seasonality of sales and site traffic demand as well as whether the current inventory levels are overstock or under-stock. This will lead to the most ‘optimal price’ and not simply the lowest price. At CalmSea we call this process Continuous Merchandising TM, and our mission is to help retailers optimize every merchandising decision — from product assortment to pricing, promotions and inventory — by combining their data with competitive pricing information and partner data like Omniture.
Q: CalmSea has built a solution that can look at large volumes of data and determine things like optimal price for a given product or optimal markdown for an overstocked item. How does the integration of online analytics data help you achieve this?
A: Online analytics data is an extremely critical piece in making pricing decisions. Many tools today try to predict demand based on historical sales transactions while ignoring the portion that did not convert into sales — what we call as latent demand. Online site analytics provides valuable contextual data around why the prospect did not convert, their preferences and where they came from, to complement merchandising and supply chain data. For example, it will help pinpoint if the problem is with a lack of site traffic demand generation or with conversions due to a pricing problem. We can thus drive holistic pricing decisions that will drive more conversions thereby improving the bottom-line for the retailer.
Q: What specific online analytics data from Omniture are you planning to integrate with your system?
A: At CalmSea, we are interested in all pieces of data that help our customers optimize merchandising decisions. We believe that Omniture can cover the entire marketing side of the equation. For starters we will pull metrics like basic site traffic and conversion data to help us optimize the price point, while location specific site traffic data helps us drive localized pricing for customers who want that. We combine the same data with inventory and historical sales data to predict future over-stock or under-stock situations. In addition, we can leverage the click-stream path analysis to discern product affinity that in turn can be used to drive bundled promotional offers and product assortment planning for the next season. We think we have only scratched the surface, there’s so much more we can do with things like marketing campaign effectiveness metrics.
Q: Once a customer is up and running, how long does it take for them to get predictive feedback on pricing and assortment from your system?
A: It typically takes us a week or so to get a mid-sized retailer up and running. Once they are up they get visibility into their business metrics immediately. They can also start managing and optimizing prices and promotions immediately. Our science platform is a self-learning adaptive platform and the decisions will improve with time.
Q: For the typical online retailer, what do you expect the impact from deploying CalmSea will be in terms of margin improvement, top-line revenue growth, etc?
A: This kind of solution has proven ROI for the brick-and-mortar retail space. Many of us in fact come from companies that successfully built such software products and sold to customers like Safeway, BestBuy and Walmart. Such solutions have proven up to 15% improvement in revenue and margin. The online world, we believe, provides many more opportunities to improve on this because of newer marketing channels and more efficient merchandising actions like real-time price changes. Our work with our initial beta customers tells us that we will see significantly better numbers in online retail.
Q: While offline retail is still the majority of dollar transactions, the online channel is becoming a significant part of the retail experience. Is there an opportunity for online analytics to influence offline merchandising?
A: I think you hit upon an important ongoing macro change in the market. Today 40% of all offline retail sales (USD 937 billion) are influenced in some way or the other by the online channel. By 2014 this number will be 54%. So online retail expands beyond just what you sell through the online channel. For multi-channel retailers there is a huge opportunity to optimize across the two channels using the strengths of one to compensate for the weaknesses of the other. For example, one of our apparel customers uses the low-cost strength of the online channel to test new products for consumer preferences by location and then stock appropriate products in physical stores. We believe Omniture and CalmSea are at the heart of this macro-movement.
Q: On a technical note, you’ve built your application in Adobe Flex. It’s a beautiful, clean interface…but beyond aesthetics, why did you choose Flex as your development platform?
A: We have been extremely satisfied with the Flex framework and the community around it. Aside from the aesthetics I would say that the productivity it provides is phenomenal after the initial learning curve. The pre-built components and open-source work atop the Flex framework have hugely reduced our time-to-market.
Q: Besides analytics, what else is on your integration roadmap with Omniture?
A: Beyond online analytics we see two major areas of integration in the near-term. First, we plan to integrate with Omniture’s Test & Target module to enable easy A/B testing of price changes. Second, we plan to integrate with Omniture’s merchandising solution to provide a complete solution that includes analytical tools as well as execution tools.