For the past centuries, companies focused on improving the customer experience during the buyers, B2C and B2B, decision-making process. This process refers to the 4 common steps leading up to a purchase: need awareness, information, evaluation, and transaction. In most product categories, however, the process of buying is significantly shorter than the last stage of the customer experience, i.e. the use phase. In the automotive sector, for example, a consumer will spend 1 to 3 months deciding which new car to buy and then drive that car for at least 3 years. In the home appliance sector, the decision-making process is typically concluded in weeks, whereas the use phase can last a decade or more. Certainly, companies tried to reinforce the relationship with the customer post-purchase with communications like standardized cross-sell offers and periodic service reminders, but these communications were seldom valuable to the customer, because they were based on generalizations and did not reflect actual product usage. The only truly valuable post-purchase moment-of-truth for companies became customer feedback in the form of a testimonial or complaint. Most companies erroneously celebrated no response as quiet satisfaction and some companies actively solicited feedback, which was seen as an opportunity to engage the customer, albeit reactively. Social media exacerbated the post-purchase relationship for many companies by giving customers the ability to share product opinions with hundreds or thousands of followers and friends, thus giving birth to a new industry in social monitoring, and a new class of customers like the the ego-poster or the professional reviewer. But the ability to monitor customer "tonality" in near-time does not change the problematic paradigm, namely, the post-purchase customer experience is predominantly reactive.
The Internet-of-Things is profoundly changing the way companies interact with their customers in that it is enabling a post-purchase relationship that did not previously exist. By connecting devices to the internet, companies can gain insights into product performance and, more importantly, individual customer behavior. The data created by connected devices is a new form of "internal data", which is the term given to information that only one company has access to. Internal data can be used to create a competitive advantage, because (a) no competitor has this information and (b) it has valuable proactive applications. To maximize the value of internal data, it needs to be used in near-time to create a personalized, post-purchase dialog between the company and the customer. This dialog can help the customer to increase a products real value as measured by benefits/costs. The measurable values include lowering environmental impact, improving safety, increasing performance and productivity, improving product uptime, extending product life. Internal data can also help the company to identify new sales opporuntities, steer product development and even create new revenue models.
In the series of short articles to follow, I will describe the proactive applications of data generated by IoT systems as business cases. The most common application of IoT is predictive maintenance, which is only one benefit and, in my eyes, not the most salient use of internal data. To draw attention to the other business benefits of IoT, I start with lowering environmental impact.