Within the past couple of years, companies have greatly changed their mode of operations. Since organizations are adopting new ways of operation, does it mean you should also change your ways? This is a million-dollar question that you should always ask yourself.
The reality is that establishing a robust technological business can service the headwinds across the industry during tough times. There are multiple data-driven organization examples that are thriving across the industries. Given that people are diversifying their business approaches, you also need to adapt to the change and make your approach unique.
However, the sad reality is that transitioning your company to a data-driven organization is not an easy task. You need a strategic approach to propel your efforts in the right direction. Remember that data only works well if you have the right technology. The immediate step is to ensure that you have the right technology operating system that will generate meaning out of the data.
This article highlights the top data-driven organization examples that you need to know. Do you want to learn more about data-driven organizations? Read this article to the end!
Starbucks:
Do you plan to open a store location? Where do you want to locate it? These two questions are the most difficult someone can ever ask you! Starbucks is known to have the solution to such questions, and it can help you address them fully. The organization uses social data and location to help you choose the best locations to locate your store.
The locations are mainly identified depending on the customer profile. Starbucks works hand in hand with other organizations to acquire more resourceful information. The collaboration has made it easier for Starbucks to consider factors such as demographic information as well as traffic flow information. This has made it easier for the company to choose better locations in new areas.
Apart from choosing the best location, Starbucks helps choose the best products that work well in the given areas. Remember that the highly-priced products perform better in the coffee-obsessed areas since people are always willing to pay higher. Keep in mind that not all products perform better in all areas. The rate of consumption depends on the consumers in the area.
Using this information works as a proper cost-saving methodology to prevent companies from channeling resources to areas where there is poor performance. Also, it’s a good approach to use when you want to optimize prices in different locations across your target market.
Note that Starbucks has been in action since 2014, and it’s still working effectively. In addition, it’s still one of the market leaders since it has managed to mitigate the competition within the business sector.
Zendesk:
Zendesk is considered a fantasy in the data science field. The organization has positioned itself in a manner that it only sells itself in a specific point system. Furthermore, it works in a way that it only forecasts sales within two percent. This is what makes Zendesk unique from the rest and the best.
The organization works by considering individual behavior and other key considerations within the sales process. When using these criteria, you will have to operate with a scale of 0 and 2. When you record the 0 scores, it means that the team members haven’t talked to the customer. 1 shows that they opted to talk to your competitors, while 2 means that they mentioned the competitor.
This information is all you need to predict revenue within your business. Note that if the mode of data collection is not standardized, you cannot establish a predictive business model. The only way to make work easier is by standardizing operations to make it easier to predict revenue. Creating an accurate predictive model is difficult unless you have a reliable backup.
But, if you introduce this model to your business, you will find it easier to determine the landscape of the business. Zendesk is growing considerably, serving clients from different locations across the globe. All you should learn about this organization is to play around with the scores and determine your business progress.
Disney:
Data streaming is a common thing that has gained a lot of significance since people started streaming TV shows. Disney has established a unique data-driven approach that is tailored to handle cases of data silos. Disney can collect information from different corners to improve information delivery and offer better recommendations.
The organization has increased the rate at which information is accessed, driving a data-driven culture within different organizations. The organization’s ultimate goal is to enhance machine learning and ensure that information is delivered in real-time and processed effectively.
In addition, it ensures that every individual within the organization gets access to accurate information in real time and when needed. The organization has greatly contributed to the success of data enablement. Disney facilitates Information delivery across developed companies such as Amazon. It used the information generated within the company to determine various aspects, such as fraud detection.
Disney can also help to enhance personalization and detect data insights and trends. Generally, the organization offers all the basic requirements you need to get the best out of your business data. It offers real-time data to its users at any time and any point. Disney uses its schema to get the most from the data provided.
Adobe:
The truth is that only a few companies can define the entire customer journey flow and map it against the marketing initiative applied. This becomes a challenge to the marketing department since they cannot facilitate broad campaigns. Adobe offers exactly what you are missing, adding the flavor you have always wanted.
The organization helps you to shed light on the entire customer journey increasing the target KPIs. Learning more about the customer journey enables the company to tailor targeted approaches that target specific customer profiles. As a result, this increases the customer action towards the required call to action.
The data-driven company tailored the customer journey approach using a series of aspects. This includes measuring the customer engagement rate, how to engage with the customers, and detecting if the engagement is successful. This strategy is applied when you want to solve any business problem revolving around the data collected.
Adobe contributes to the success of data science projects since it explains the entire scope of the project. The organization sets up the best data-driven marketing strategies to generate better results. Even though Adobe took time before hitting the ground, everything is currently working smoothly.
Conclusion:
Establishing a data-driven organization requires you to have robust acumen. Before you set up everything, it takes a lot of time and effort to create data-driven by-data values and decisions. However, if you have an awesome data approach, you will likely establish something reliable that will generate valuable returns. You should take the right technology approach to make your efforts successful. Research is a key aspect you need to consider before setting up anything. You need to find out detailed information regarding every move you make. Proper use of data can heavily contribute to your organization’s continued growth and development.