Product manufacturers are increasingly transforming themselves into service providers through the deployment of the Internet of Things (IoT). IoT monetization, however, is proving to be difficult not only because data acquisition, aggregation, and analysis create additional layers of pricing metrics for these manufacturers, but also because most economic benefits are realized progressively and over time. This new time dynamic of value creates the risk that the one-time-sale product providers leave money on the table with their new IoT offerings.\nThis was the subject of a recent discussion I had with Esra Kucukciftci, CEO of Pricing Innovations \u2013 a product and monetization consultancy focusing on technology products. Esra has been working on pricing strategies with her customers over the last five years and has found IoT based offerings do not fit the normal processes and rules of pricing.\nThe fundamentals of monetization\nSN:\u00a0 Esra, as both a physicist and business leader I like to start with fundamentals, Newton\u2019s Laws and Supply vs. Demand so to speak. How do you describe the fundamentals of monetization upon which you build pricing models?\nEK: We too always start with the fundamentals, in this case the Golden Rule of Pricing:\n\u201cDevelop offerings that people will acquire, for a price commensurate with the benefit delivered, at a cost structure more favorable than the competition.\u201d\nAs with all good fundamental advice this seems simple. But connected product manufacturers are subject to new assumptions: real-time data availability, adaptive implementation, and value propositions from data not yet used by operations. Further, the perceived value varies significantly because customer buying, and usage models differ even within a segment.\nSN:\u00a0 I have always stressed how segmentation is a key to developing good IoT offerings because of the precision of the technology.\u00a0 By that I mean how easily a given IoT offering can adapt to a specific segment need.\u00a0 Of course, in this case, precision means that broad base pricing won\u2019t work as some users will perceive much more value than others. \u00a0How do you help your customers get started in their pricing design?\nEK:\u00a0 Fundamentally buyers acquire solutions when the value they receive surpasses their cost. \u201cPrice\u201d defines the point at which the value exchanges hands -- where the buyers gain a surplus of benefits and the providers gain a surplus of profits. Optimizing the point of exchange for IoT offerings requires a quantitative understanding of how different buyers require, acquire, and realize the benefit from the offering differently.\nA quantitative approach to segmentation in IoT is critical because the business workflows, products and services that result from the data can vary significantly across customer types even when the data comes from the same sensor and is delivered through the same information infrastructure. As a result, an IoT vendor can charge more for some segments of the value chain with one customer and not at all with others even though the technology offering is the same.\nConsider the value chain of an IoT-based tracking and monitoring solution for supply chain applications above. While the technology itself can be packaged agnostically for warehouses as a supply-chain segment, the value perceived by customers within that segment may vary significantly.\u00a0 A high mix durable goods operation, for example, will value identifying and tracking very highly \u2013 for enhancing cycle times and reducing lost-item costs.\u00a0 A low mix perishables warehouse operator will value environmental and shelf life most highly because those factors drive customer satisfaction and scrap-loss costs.\u00a0\n\u201c\u2026delivered at a cost structure more favorable than the competition\u2019s\u201d\nSN:\u00a0 So clearly monetizing such a solution requires the IoT provider to segment their markets vertically \u2013 based on value delivered to each segment, instead of horizontally \u2013 based on business size or industry types.\u00a0 But this reveals a new challenge IoT vendors face: value delivered is built on the analysis for actionable use of data and is thus flexible, customizable, and scalable.\u00a0 The value of the data will be relative between different customer segments as well as along the value chain. Accordingly, the better a vendor understands how the benefits of their offerings are realized by customers, the better they will be able to maximize the value captured from the IoT offering. \u00a0\nI understand you have adapted your pricing analysis of the value chains into a new tool to help with IoT pricing.\u00a0 Can you tell us about that?\nEK:\u00a0 Yes, we use Value Stack Analysis to help our customers better understand both the detail and timing of the value of their data-based offerings. A value stack is exactly as it sounds \u2013 a stack up of economic value delivered throughout the customer\u2019s engagement with the offering.\nSN: So, the value stack approach allows for customization both by and within segments without changing the structure of the offering.\u00a0 But as I see it, once a pricing structure is defined, companies must still have solutions that deliver the corresponding value stack and do so with a cost advantage. \u00a0However, cost structure is a surprisingly difficult challenge for IoT providers. The problem isn\u2019t the hardware cost; Moore\u2019s Law has made the COGS (Cost of Goods Sold) almost insignificant.\nEK: That\u2019s absolutely right. In our experience, we see that the big problem is the wildly varying costs of ongoing delivery for the supplier and of overall implementation for the customer. Integrating with the legacy systems, solving for predefined hardware constraints, implementing new types of technical and business decisions, and managing change don\u2019t usually scale linearly with a feature block or the size of the operation.\nSN: So in that sense, complexity could be a good source of price differentiation and must be integrated into the value stack analysis.\u00a0 How do you suggest manufactures do this?\nValue stack analysis enables a \u2018monetization-first\u2019 approach to building IoT offerings\nEK:\u00a0 The short answer is \u201cwhen\u201d pricing comes into the picture. A pricing-first approach to solution development is key to not only developing solutions that you can sell but also to making informed trade-off decisions throughout the life cycle of the offering. That\u2019s why the value stack analysis can help:\n\nThe analysis forces an identification, sequencing, and quantification of the economic benefit for each value function across primary customer types.\nThe value structure is converted to an offering structure that aligns both cost and perceived value for the different segments thereby optimizing value delivery.\nThe offering structure then informs the pricing structure that optimizes customer adoption and profitability.\n\nThe value stack analysis not only aligns the value functions of an IoT solution for optimum value delivery but also supports the technical decisions for developing the most profitable offering, early in the development cycle.\u00a0 When the IoT monetization strategy adapts to the different segments, the provider finds their success metric tightly linked to those of their customers and growth becomes exponential with both number and growth of those customers. \u00a0Aligning your revenue model with your customers\u2019 benefits is where the opportunities to innovate pricing lies.\nSN: That last point seems to be \u201cthe prestige\u201d of the whole process.\u00a0 As I said above, I like working from fundamentals and there is no better way to grow a business than to have customers who are growing. What\u2019s great about the value stack analysis approach to IoT pricing is that as a supplier, these companies can play a much more proactive role in helping their customers grow.\u00a0 The ultimate win-win in business.