SITUATIVE RELEVANCE INDEX — new generation customer value proposition
The “Coca-Cola formula” of every company to maximize customer satisfaction
SRI — What is it?
The Situative Relevance Index (SRI) is a methodology to dynamically simulate the customer value proposition. It is based on customer and contextual real time data, evaluated by an artificial intelligence algorithm to predict future customer behavior. Furthermore, and in comparison to today’s customer value proposition methodologies, the system is able to create on-the-fly situative relevant services to customers that will lead to an Ultimate Customer Experience (UCX) through service excellence.
As the SRI can be considered to be a cloud-managed platform or smart ecosystem, it can be adapted to any specific enterprise and market, aligned with their business strategy or customer interaction plan. It also offers third party access wherever it makes sense.
Today’s methodologies are mainly based on historic data from customer surveys, market research or focus groups. Quite often this data is assembled in an analogue form, making analysis inefficient and low-yield. Using big data, artificial intelligence and the internet of things can not only make this process real-time, it also makes it more effective, efficient and satisfying — for the customer and the enterprise. Instead of living in a world of linear customer data collection, which creates limited, slow, and stale data sets, organizations can harness an exponential stream of affordable real-time behavioral data.
That flood of customer data empowers companies to focus on making continuous improvements to their internal customer management and marketing systems, saving time and money while increasing productivity and consistency aligned with customer service excellence.
Where did the SRI idea come from?
The idea for the SRI resulted in the use of digital technologies and the necessity to create the next generation of a 360° customer-centric value proposition models. The whole approach is based on scientific research for advanced customer centricity modeling by Professor Wolfgang Henseler (University of Pforzheim, CEO of Sensory-Minds) in cooperation with Amazon Lab 126 and an Amazon customer-centricity and artificial intelligence „Two-Pizza Team“. A Two-Pizza Team is a workforce that defines its own business plan, metrics and product roadmap in the SRI case service and customer interaction roadmap.
Amazon’s corporate vision statement „to be earth’s most customer-centric company where customers can find and discover anything they want“ was the starting point for the SRI. The goal was to create a predictive customer value proposition system to maintain competitive advantage by creating the utmost user experience through a state-of-the-art customer excellence instrument.
A customer-centric AI-based value proposition model
The SRI can be regarded as an artificial intelligence-driven customer-centric ecosystem using any data touch point and data source (e.g. smartphone apps, websites, IoT devices, retail or product, ERP- or CRM-system etc.) connected to the ecosystem to collect big data and analyze it in an SRI cloud-based entity. Using machine learning, e.g. Amazon Kinesis, SageMaker or any similar third party solution with company-specific SRI metrics the system can be used to offer the best products and services in class.
In contrast to the SRI as a customer-centric value proposition model and not a customer-oriented or product-oriented one, existing customer evaluation models from Kano or methodologies like the ABC customer analysis based on Pareto rules, the Net-Promoter-Score by Reichheld or any market research and Customer Satisfaction Index (CSI) will not be able to result in a personalized real-time customer scoring or value hedging. The capability to use continuous real-time customer data for marketing, trade, production and logistics gives companies huge advantages. In a world of rapidly changing customer expectations a company that can effectively, efficiently and satisfyingly address customer future needs will have a competitive advantage. The SRI will be the foundation for the aspirational goal of zero provisioning in order to bring your customer experience to perfection.
The core of the system
The SRI is based on a company-specific set of metrics that is organized in an SRI scorecard. The scorecard contains all the key performance indicators (KPIs) as well as the customer performance indicators (CPIs) — see also our article on Behavioral Analytics. It builds the foundation for the initial algorithmic training and continuous refinement. It also contains general target settings for the customer relevance-driven services. The other components are a cloud-based database, either corporate or third party, e.g. AWS, and SRI-specific machine learning modules to analyze data, find patterns and generate on-the-fly situative relevant customer services. The whole system is designed to create the Ultimate Customer Experience (UCX).
Data usage and protection
As the SRI is a customer-centric and not a customer-oriented or product-oriented value proposition model, gathered customer data needs to be protected by the highest standards of data security and data protection e.g. GDPR or PEPP. Therefore the SRI data protection architecture has its foundation in the Amazon Data Protection Guidelines, one of the highest data standards in the world.
The goal of the SRI
The SRI is a strong „tool“ to better incorporate technology to serve customers better, to enable new business capabilities, to adjust efficiently to the market, to drive an organization’s vision and to orchestrate competitive advantage. Predicting future customer needs and exceeding customer expectations will become crucial to any company in the digital era. Therefore, being digital means using innovative technologies, gathering big data and enabling machine learning for real time scoring, in order to offer the best user experience in place.
The effect of the situational relevance index — the Ultimate Customer Experience — is also reflected in the market value, as companies like Amazon, Apple, Google, Facebook, Tesla and Co. have only been demonstrating for years.
To summarize:
The better the SRI, the more successful the enterprise will be.
Similarity to robo-advisors in the financial world
Robo-advisors are a class of financial adviser that provide financial advice or investment management online, with moderate to minimal human intervention, based on mathematical rules or algorithms. These algorithms are executed by software — thus financial advice does not require a human advisor. The software utilizes its algorithms to automatically allocate, manage and optimize clients’ assets. Robo-advisors typically allocate a client’s assets on the basis of risk preferences and desired target return. While robo-advisors have the capability of allocating client assets in many investment products such as stocks, bonds, futures, commodities and real estate, the funds are often directed towards ETF-heavy portfolios. Clients can choose between offerings with passive asset allocation techniques or active asset management styles.
Similar to a robo-advisor, where the customer financial portfolio and its assets e.g. stocks, bonds, futures etc. are managed by an algorithm to grow financial value, the SRI will manage the asset class “customer“ and its customer value proposition. It utilizes algorithms to analyze, manage and optimize customer data to offer best in class service resulting in the ultimate user or customer experience — comparable to the ultimate financial portfolio but with your customer and his or her value as the asset.
Summary
In order to be able to act successfully in the digital age, our mindset of, for example, the user- and customer-centered thinking has to be brought into line with the skillset of using self-learning algorithms and artificial intelligence. This is because only if both approaches have been perfectly aligned you can create the difference that ultimately achieves the competitive advantage for the customer — the Ultimate Customer Experience.
© 2020 PROFESSOR WOLFGANG HENSELER — SENSORY-MINDS GMBH Version 0.31
Prof. Wolfgang Henseler (born 1961) is founder and managing creative director at SENSORY-MINDS, a design studio for New Media and Innovative Technologies based in Offenbach am Main (Germany). He is a professor for Digital Media and an expert in Digital Transformation, Natural User Interface Design, Ultimate User Experience and Usability — and the dean for Intermedia Design — the design of smart objects and the Internet of Things — at the University of Pforzheim — Faculty for Design.
For more than 20 years Professor Henseler has worked and done research within the areas of User Centered Interface Design, digital Brand Experience and Usability. Based on his research in user- and consumer-psychology he has developed different methodologies for optimizing digital infrastructures as e-commerce or e-business systems. His capabilities in digital transformation and Industry 4.0 is in demand by enterprises like Mercedes-Benz, JTi, Deutsche Bank, Lufthansa, Porsche, RWE, SAP, Volkswagen and others. When it comes to next generation ecosystems and business innovation Professor Henseler can be mentioned as one of the most visionary persons and consults enterprises like Apple, Amazon, Google and Microsoft in the field of Customer Centricity, Ultimate User Experience, the next generation of Human-Computer-Interaction.
Get in contact:
Prof. Wolfgang Henseler | Managing Director Innovative Business Development @ Sensory-Minds
w.henseler@sensory-minds.com
