BBVA API Market
APIs are the beginning of a good user experience: they reduce response times in uploading data on an interface, automate processes with a native format within applications and facilitate interaction with other applications within a platform, etc.
As a result, they speed up interactions and functions of the digital products that users work with on a daily basis. This is true of social networks such as Facebook and Twitter or of content distributors and producers such as Netflix and HBO, as well as the virtual assistants Siri and Alexa, provided by Apple and Amazon, respectively.
For companies offering internal or third party API services, almost everything comes down to single question: Does it improve the customer’s experience? And following from there: Does this good experience improve business metrics?
Today almost all digital products can be included in four major categories of metrics:
Some of the most useful metrics in this category are the volume of unexpected closures of an application the response time of the API that loads the data onto the interface, end-to-end response time (if this time is between 3 or 4 seconds, the customer will probably interrupt a given task, such as purchasing a product in an e-commerce), loading time (this measures the volume of responses that can be provided to users of an app over a particular period of time – concurrence-), network errors due to excessive API response times and so on.
Some of these metrics are the number of active users both daily and monthly (which should always grow steadily, especially in business where monetization depends on a steady increase in user acquisition), metrics related to the operating system used for the application and geo-localization metrics, which are key in sectors such as retail and content.
The concept of engagement includes some of the most important user experience metrics, such as session time, the time interval between sessions, user retention rate and the percentage of rebound. All these depend to some degree on factors such as performance, which is derived from API behavior.
Technical factors result in better engagement metrics, as well as in better business metrics. Optimal performance of APIs for customers, partners and suppliers results in continuous improvement of metrics such as the cost of customer or user acquisition (APIs enhance business model outsourcing and viralization, which boosts acquisition and reduces the associated cost), task abandonment rates (a critical metric for businesses associated with transactions) and the lifetime value (LTV) or net value of the income generated by each user.
If we analyze the primary sectors of advanced economies, the impact of APIs is enormous in relation to success stories in the creation of new business models and productive channels of income.
We will review some practical cases that perfectly illustrate the value of APIs:
Theatre Direct (LTD), the company that sells London theater tickets, sought the help of the TIBCO Software company, with the support of the Mashery API Management company, to create an API_Market to provide services to suppliers and consumers. This API_Market provides the use of open APIs and the API Manager monitors the services.
Some of the benefits of the London Theatre Direct API:
The idea is to connect passengers with the platform’s flight and price comparison system, one of the most widely used in the world. This customer service improves user experience significantly.
It is not the only case of an air transportation company that uses APIs to improve the lives of its customers.
Alaska Airlines was one of the first to develop an application for iPhone that provides access to boarding cards with the help of an API.
Affinio is a company that plans and implements marketing strategies for different brands. Their case is special because the company was founded on the idea of using the Twitter API to become familiar with their audience and to find new customers and better business opportunities. Their social network interface enables the generation of user segment charts grouped by interests (clusters) and to plan custom campaigns around these.
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