DAIL
A New Perspective For Platform Economies
- Introduction
The platform economy is economic and social activity facilitated by platforms. Such platforms are typically online matchmakers or technology frameworks. By far the most common type is “transaction platforms”, also known as “digital matchmakers”. Examples of transaction platforms include Amazon, Airbnb, Uber, and Baidu.[1] Many of these companies’ most groundbreaking innovations are not products or services; they are the platforms on which these products and services are built and the business models that these platforms enable. Such platform-based business models fundamentally change how companies can do business.
Platform-based business models allow companies to create entire ecosystems that do much of the work to grow the company and drive strategies. The platform has become the business model that is opening up entirely new paths to growth for companies. While tech companies and the born-digital have successfully mastered platform strategies, the opportunity is now opening up to every company in every industry.[2]
It is seen that companies accept platform-based business models that have made irrefutable progress in the global economy. The unparalleled growth of the digital economy has put it on course to account for 25 percent of the world’s entire economy by 2020, up from 15 percent in 2005. As this growth continues unchecked, platform business models represent a “fast-increasing” proportion of the overall total. The top 15 public ‘platform’ companies already represent $2.6 trillion in market capitalization worldwide. [3]
As of 2018, Amazon is the most valuable brand in the world with a daily sales volume of over $410 million. If Amazon examined as a platform-economy based model, the key inferences can be mentioned as, evaluating the user data correctly and implement solutions, using artificial intelligence applications from production to personalized recommendations offered in product sales and providing special opportunities with loyalty programs, Prime is an example for Amazon Loyalty programs –a paid subscription service offered by Amazon with over 100 Million users-.
After examining the platform-based companies, some key methods have been found as enabling them to achieve this level of great success in a short time. These methods include the collection and processing of user data, the generation of artificial intelligence-based solutions appropriate to the processed data, the implementation of the solutions to provide maximum benefit in the shortest time and the providing sustainability of this digital ecosystem by combining these methods. In this ecosystem participant companies-partners of platform-, gain some abilities like, how to provide customers retain in the ecosystem, how to increase customer activity, how to evaluate needs, and suggesting different products for customers continuously. We have identified essential methods for building a platform-economy based ecosystem. Those are data, artificial intelligence, implementation, and loyalty programs. We develop a model, which uses those methods to build a platform-based ecosystem named DAIL.
2 DAIL
DAIL model consists of 4 core components that enable the ecosystem to work and improve continuously. All of these components are interrelated and need to work together to maintain the ecosystem.
The main purpose of the DAIL is building a business model for the continuous improvement of products and services in a platform environment. The first 2 steps of DAIL is to collect data from user actions, choices, transactions then analyze them and achieve meaningful consequences like personalization, behavior analysis, cost reduction, variety, price optimization, improving performance and logistics optimizations through machine learning techniques. Therefore, the participant companies will have new opportunities to create and to develop new products and services in the platform.
DAIL model enables the companies in the platform to evaluate the needs of the market and develop new products. It is critical to implement these products at the right marketing time with high efficiency. For this, the system must be built on modern, flexible and strong infrastructures.
After generating an ecosystem from this perspective, it was deemed necessary to create a cycle for users to stay in the system continuously. For this purpose, loyalty programs come into play in which continuity can be ensured by offering privileges to the users. In DAIL, by the modern infrastructure which the system will be built on, the privileges -such as loyalty points can be used in purchases on a particular company- that customers obtain on a member of the platform may also apply to other business partners on the platform. To provide this and the safety of customers data, it may be useful to develop the system on blockchain-based applications.
2.1 Data
Data is an essential element for using artificial intelligence algorithms in the platform. In a platform-based business model, essential data can be generated by platforms’ own. The platform can handle multiple data points from a large of sources, and the data is gathered organized in the platform instead of each firm has own data separately.
The data gathered in the platforms can be classified as, identity data, descriptive data, behavioral data, transaction information, online activity information, opinion information, attitude information and more as the platform grows.
Platforms can help forward-thinking marketers organize their data, enhance their audience segmentation and campaign planning, increase content engagement, streamline cross-channel marketing orchestration, and optimize analytics efforts. Strategy and cohesive technology solutions are vital to long-term success.
Using the meaningful data provided by the platform is a great advantage for participant companies which helps them to get rid of spending time and energy of gathering data on their own.
With a greater understanding of customer needs, as well as the ability to anticipate future needs, companies can develop new products and solutions for their customers. In a platform-based business model, more neat and meaningful data provides lots of advantages for companies to deal with the competitive market.
2.2 Artifical Intelligence
Artificial Intelligence(AI) is the field of computer science dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem-solving, and pattern recognition
The ability to analyze data and predict customer wants based on analysis is one of the most important applications of artificial intelligence. AI-driven personalization has a high success rate. Also, deep learning -an artificial intelligence method- refers to machines programmed to predict outputs based on data input. When applied to engaging customers, this technology can maximize customer personalization and therefore greatly boost the customer’s experience with sites, products, or stores.
There are some remarkable statistics about AI, the first point is the revenue of AI. The economic impact of AI will be driven by (a) productivity gains from businesses. According to McKinsey’s 2018 September report, AI could lead to gross GDP growth of around 26 percent or $22 trillion by 2030. The major contributors to this figure are the automation of labor, which could add up to 11 percent or around $9 trillion to global GDP by 2030, and innovations in products and services, which could increase GDP by about 7 percent or around $6 trillion by 2030. The second point is about the interests of the market. According to a survey by Brightedge, 29% of marketers believe we are trending towards consumer personalization and 26% believe we are trending towards artificial intelligence. In a few years, using artificial intelligence to create a more personalized experience will be the new norm for retailers.
Businesses use AI for marketing personalization because of returns like improved customer experience, delivery of better content, offers, and experience, improved performance metrics, increased productivity, more accurate personalization, increased work quality and more.[4]
As an example, Netflix processes the big data to serve customized content for each customer. Personalization helps members find content to watch and enjoy the maximize member satisfaction and retention. Netflix states, over 80% of what people watch comes from the recommendation system.[5]
2.3 Implementation
Implementation is the key step for integrating new strategies and business solutions into the systems.
Up to this stage, platform participants produced various results by processing the data they obtained with artificial intelligence-based algorithms.
In this phase, understanding the concept of time to market is crucial. Should be reminded that delay in the commercialization of a product can be a deal-breaker. The majority of innovations are technology dependent or enabled. For a company, to work well and efficiently come up with the right innovations, in implementation phase companies have to choose the right systems for their business.
In order to shorten the integration process and ensure higher efficiency, the system needs to be built on modern and reliable infrastructure. This infrastructure should facilitate the realization of other steps of the DAIL model and make it more effective. The experience gained during the integration phase is valuable for the self-training of the platform and the optimization of subsequent processes.
It is important to remember that DAIL’s suggesting platform business model needs to be able to handle scale, security and data variety because edge data is becoming a larger component of customer data.
For providing those mentioned specifications, blockchain-based solutions are suggested. By building a blockchain-based ecosystem, decentralization of data can be provided. Each party on a blockchain has access to the entire database and its complete history. No single party of platform controls the data or the information. Every party can verify the records of its transaction partners directly, without an intermediary.
2.4 Loyalty
Loyalty is a customer’s attachment to a brand, store, manufacturer, service provider or other entities based on favorable attitudes and behavioral responses such as repeat purchases [6].
Loyalty programs are designed to improve customer satisfaction and commitment[7]. Customer loyalty is very essential to the organization to retain its current customers. It is because a customer’s loyalty can serve several benefits to the organization. Loyal customers are less price-sensitive, reduce marketing expenditures for attracting new customers and improved organizational profitability [8].
Unlike traditional ones, the DAIL model integrates loyalty programs into the platform, aiming to generate revenue for all stakeholders rather than for a single company without limitations. To achieve this, the customers must have privileges valid on the whole platform. Among the modern infrastructures, a blockchain-based solution is recommended for this stage in the DAIL model. Through blockchain-based solutions, reward points that can be obtained from loyalty programs can be developed in a blockchain-based token–digital assets built on platform blockchains like Ethereum, EOS, NEO- structure that will be valid for all stakeholders of the platform.
Also, various innovative campaigns, privileges, and innovations can be presented to the users with the smart contracts -self-executing code on a blockchain that automatically implements the terms of an agreement between parties[9]-. Trust plays an essential role in the formation and consolidation of business interactions and relationships. Blockchain is able to streamline execution and administration of loyalty rewards programs, giving all participants near-real-time transparency. Besides integrating with, and enhancing, legacy systems that currently operate loyalty rewards programs, loyalty Blockchain is the answer rewards providers are able to control exactly how they and their customers interact in the interlinked network to which blockchain provides them access.
3. Conclusions
The rise and importance of the platform economy in the 21st century have been seen. It is known that the firms built on the platform economy are now among the largest companies in the world[10]. The key features of the rapid and tremendous rise of these firms were examined.
These features are defined as data, artificial intelligence, implementation, loyalty and a digital ecosystem model that can be applied to create a platform economy that enables owners to increase their business capabilities. This model is named DAIL.
The DAIL Model recommends platform partners to integrate them into the system at the right time with high efficiency by personalizing customers and perpetually creating up to date solutions. DAIL Model forces participated companies to understand their customers’ needs, to develop new products or services, to come up with new strategies and to bring new technologies to their businesses.
Authors
Bülent BEDİR, İrfan AKARSU, Taha BAYAZ, Şafak Kayran
References
[1] Public Policy exigencies for Platform Economy & Social Media Regulation, Costantinos Berhutesfa Costantinos
[2] Platform Economy: Technology-driven business model innovation from the outside in, Accenture
[3] https://www.accenture.com/fr-fr/_acnmedia/PDF-2/Accenture-Platform-Economy-Technology-Vision-2016-france.pdf
[4] https://www.statista.com/statistics/915493/benefits-using-artificial-intelligence-marketing-personalization/
[5]Gomez-Uribe, Carlos A. and Neil Hunt. “The Netflix Recommender System: Algorithms, Business Value, and Innovation.” ACM Trans. Management Inf. Syst. 6 (2015): 13:1–13:19.
[6] Moormann, Jürgen & Roßbach, P. (2001). Customer Relationship Management in Banken.
[7] Keh, Hean Tat & Hwai Lee, Yih. (2006). Do reward programs build loyalty for services?: The moderating effect of satisfaction on type and timing of rewards. Journal of Retailing. 82. 127–136. 10.1016/j.jretai.2006.02.004.
[8] Rowley, J. (2005), “The four Cs of customer loyalty”, Marketing Intelligence & Planning, Vol. 23 №6, pp. 574–581. https://doi.org/10.1108/02634500510624138
[9] John Ream, Yang Chu, and David Schatsky, “Upgrading blockchains: smart contract use cases in industry,” Deloitte University Press, June 8, 2016.
[10]https://milfordasset.com/insights/largest-companies-2008-vs-2018-lot-changed
