10 Tips For Building A Data-Driven Business
Many successful businesses today rely on data analytics to make decisions. And those who fail to do so are likely to fall behind. Aside from this, data is crucial for developing strategies, gaining customer insight, improving customer retention, and boosting revenues and profits.
However, 41% of businesses report struggling to turn data into useful information for decision-making. Unfortunately, this doesn’t help but drag business efforts. Below are some top tips for building a data-driven decision-making business.
1. Understand what it means to be data-driven
Data isn’t only a consequence of transactional systems in today’s business climate. Most technologies and applications are designed to enable organizations to make better decisions. As a result, you cannot afford to collect data and not use it immediately. Therefore, it is advisable to build systems that allow decision-makers to access data for that purpose.
A business that takes a “data-driven” approach is more strategic when relying on accurate interpretation and analysis. This allows them to review and organize their data to better serve their clients and consumers. This doesn’t mean rushing through things. Instead, ensure the analysis is done through a step-by-step, reviewed process for the best outcome.
2. Begin from the top
It is easy to assume that building a data-driven business only involves tech companies. However, it is equally important for those in other fields, including catering and transportation services. Being data-driven requires commitment, energy, and focus throughout the business.
Undoubtedly, you may not have enough resources to commit to becoming more data-driven at first. However, it is still crucial and must begin from somewhere. And where else to begin than at the top of the decision-making chain? The entire business, including employees, will appreciate the importance of data when leadership champions the initiative.
Your staff, in particular, will feel empowered if you build an infrastructure that thrives on transparency while using objective factors to make quick and confident decisions. And data allows you to do that.
3. Stay focused
A lot of data is generated from your daily operations and client interactions. When you examine how much you’re already gathering, you may easily become overwhelmed, confused, or misled by all the metrics. So consider your business objectives and prioritize the numbers you need to monitor.
For example, although ingredient prices are essential for running a coffee business, they have no bearing on whether or not you should build a drive-thru-only store. You’ll need to ask relevant questions and make decisions based on the data you gathered.
For example, how much time do your staff members spend on average servicing a buyer at the window vs. the counter? What service channel has the highest average order value? Once you’ve established a goal and gathered the relevant data, you can quickly evaluate and make well-informed decisions.
4. Train staff on how to correctly interpret data
Nobody is born data literate, but you need everybody to be on the same page to build a business that makes data-based decisions. Every employee should have knowledge on whether they are utilizing data-driven goals, metrics, and recommendations appropriately. This may be challenging in a field where terminology is sometimes imprecise.
For instance, the terms artificial intelligence and machine learning are frequently used interchangeably, some experts say. However, training your staff on correctly interpreting data enables everyone to use it in a way that is easy to communicate and understand. This forms a part of the change that must occur if you want your business to genuinely be data-driven.
5. Look at the bigger picture
You can perform analyses on multiple levels and examine findings from numerous data sets to see the broader picture. For instance, you can’t only consider which customers pay the most money if you want to find out your most profitable clients. It can be useful to also examine how much it costs to service such customers and their estimated lifetime value.
Finding answers to these key factors necessitates multivariate analysis, which might be difficult. It is vital to determine the dependent variables and learn if there is a negative correlation between customer lifetime value and per-session spending in the prior example. And when in doubt, seek assistance from experts.
6. Develop data-driven customer experience
Customers say their experience is a crucial factor driving their buying decisions. PWC revealed this, suggesting that many people are willing to pay more for an excellent customer experience. A negative encounter could deter clients from buying an excellent product at a great price.
Therefore, pay attention to the key pillars of excellent customer experience, which are people, data, and processes, to optimize your company’s customer experience. Data and analytics can transform how your outfit approaches consumer experience by enabling you to build a more dynamic, responsive, and tailored product or service.
7. Offer data-driven products
Consider what your data says if you want to create products the market wants. The data you collect may reveal the products in which the market is most interested and how to make design and marketing decisions based on consumer behavioral data. This can be useful for making the biggest impact on sales.
You can try the following to use data to provide interesting features based on users’ recommendations, personalized ranking, and interests from particular locations. First, follow the market trends, consumer interests, and behaviors. Also, monitor the various channels customers use to search and purchase products, including devices and browsers.
8. Embrace new tech
You will likely create a culture where data is protected and hoarded if you use ancient technologies like on-site data stores and email as a major means of communication. However, using the correct technology is not always a shortcut to creating a data-driven culture. Technology and culture are two sides of a single coin since both rely on your willingness to innovate.
Companies should instead invest in a contemporary technology portfolio that includes AI-driven analytics and collaboration tools. This is frequently associated with a creative culture in which data is decentralized, openness and trust are established, knowledge and insights are distributed, and everybody feels empowered and inspired to embrace the new technology.
9. Set aside time for review
Data are merely numbers without evaluation and analysis and do not result in change. For instance, ETL, “extract, transform, and load,” allows you to enter figures into a program displaying a story. So to get the best out of your data, schedule time, like once a week, to examine the latest improvements to the metrics you’re tracking.
Different data sets necessitate the use of different analysis and visualization methods. For example, a regression analysis is more suited if you’re looking to figure out a relationship between two numerical variables.
10. Analyze your data collection methods
It is not surprising that data obsession is a secret to the success of several ecommerce businesses, including Amazon. The ecommerce business monitors 500 KPIs to ensure it has all the needed data for decision-making. Many of its projects begin with identifying trends, for instance, establishing a link between slower page loading times and reduced customer activity. This is to encourage you to create a strategy for how you collect and analyze the data.
For instance, if you own a fleet business, you can’t assume that the amount of fuel you consumed on Tuesday reflects the whole week. In such cases, investing in systems designed to make managing fleet vehicles easy by tracking real-time costs and quickly making decisions can be useful.
It is not enough to collect data if you do not use it to drive your decisions. While this may not be the easiest thing to do, it is key to staying competitive. Consider the tips above to build a successful data-driven business.