First, the Covid-19 pandemic, then the supply chain crises and the rise in inflation brought the importance of data to a new level. Having fast and reliable predictions has become achievable only by measuring the sensitivity of customers and competitors to changes in the outside world.
It is common for most businesses to analyse a lot of internal data from CRM applications, software logs, website footprints, IoT devices, and incorporate analysis results into decision processes. It’s hardly the case for external data. Looking at the outside world, more and more data sources have become available, and very little of their potential is being used by businesses.
Did you know that there’s a lot of information outside your organization that can give decision makers an edge? External data can help you understand your customers better and improve strategies for growing your business.
What is external data?
External data is any data that your company does not generate on its own. In addition to data produced by statistics departments, government, or commercial organizations, it is also generated from the internal processes of other companies, and web monitoring of the activities of consumers or competitors.
The data such as the density of people at a specific location, the stock status or discount information of competitor products on e-commerce websites, the intensity and type of interaction of a brand in social media are several advanced examples of external data.
External data is often blended with internal data to better understand macro trends, the market, and customers. It can be used for countless business use cases such as sales forecasting, fraud analytics, location analytics, price optimization, and promotion analytics.
Why should organizations use external data?
The main reason is to improve forecasting abilities. Forecasting is a key part of running any business. With better forecasting, you can anticipate changes in the market and make more informed decisions about how to proceed.
You can use external data to improve your forecasts by refining your understanding of what has happened in the past and to identify new opportunities for growth or innovation based on external data sources. This can help you discover untapped markets or identify areas where there’s room for improvement — and it gives you an edge over the competitors who aren’t using this information effectively.
Moreover, external data such as income level, spending habits, crime rate and points of interest can help organizations decide on the best location. It can provide valuable insights into how successful (or not) a new campaign or a store will be at driving sales or increasing awareness of the brand and its products or services among consumers.
As useful as the external data is, there are some challenges in using these datasets. It is often difficult and costly to try to obtain advanced external data from sources one by one. Creating a consistent stream of data, automated web scraping, managing the necessary infrastructure and creating insights and predictions requires a team of experts. Advanced external data sources require constant management, monitoring and maintenance as they are unstable and any changes on them can often break custom scraping pipelines. Moreover, if the data collected is not forecasted or is in an unstructured format, it may be necessary to develop AI models to forecast or parsing tools to make the information useful. In summary, a robust storage and processing infrastructure will be required to maintain a viable external data collection pipeline. External data service providers can be used to overcome these challenges. For needs that cannot be met with standard services project-based planning may be required.
The use of advanced external data will continue to increase since you can’t build high-quality predictive models using only internal data. Latest crises have shown us how consumer behaviour and purchasing habits can change dramatically within weeks and how predictive models can suddenly become obsolete. Providing clean, complete, compliant external data and insights can be challenging but it can be managed with cost efficient and sustainable external data services. In this blog post, I’ve covered what external data is, why it is important, why external data services are necessary and some of the ways that it can benefit you as a business owner, leader or data scientist.