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How can agencies step up their game in a data-driven world?

In 2020, the Economist newspaper published a report titled “The world’s most valuable resource is no longer oil, but data”. Following this, many experts from different agencies hailed “data” and “ data-driven decision-making “ as the next big thing in business. As more and more organizations began to notice the power of using data a new phenomenon arose: “ data-driven agencies

In the early days of computing, it usually took a specialist with a strong background in technology to mine data for information because it was necessary for that person to understand how databases and data warehouses worked. If a manager on the business side of an organization wanted to view data at a granular level, she had to reach out to the information technology department (IT) and request a report. Someone from the IT department would then create the account and schedule it to run periodically. Because the process was complex, ad hoc reports, also known as one-off reports, were discouraged.

Today, business intelligence tools and data analytics require very little, if any, support from the IT department. Business managers can customize and optimize dashboards to display the data they want to see and run data analysis on the run. The changes in how data can be mined and visualized to fit the customer experience allowed business executives who have no technology backgrounds to be able to work with analytics tools and make data-driven decisions.

Data-driven decision management (DDDM) is an approach to business governance that values decisions that can be backed up with verifiable data. The success of the data-driven approach is reliant upon the quality of the data gathered and the effectiveness of its analysis and interpretation.

Data-driven management is usually undertaken as a way to gain a competitive data collection advantage. A study from the MIT Center for Digital Business found that data-driven marketing initiatives from agencies relied mostly on data management efforts that had 4% productivity rates and 6% higher profits. However, integrating massive amounts of information from different areas of the business and combining it to derive actionable data in real-time can be easier said than. Errors can creep into data analytics processes at any stage of the endeavor, and serious issues can result when they do.

In today´s ever-changing landscape of evolving competitors and well-funded disruptors, data is undoubtedly becoming the key driving force for organizations, new and old, to stay competitive and innovate ahead.

This is evident with the ever-increasing growth in revenue of the big data and analytics software market which showed a 10,4% jump to US$67 billion in 2022 as compared to US billion in 2020.

What does it mean for an agency to be data-driven?

Being data-driven refers to the incorporation of data or information that is stored and rooted in numbers and facts, into an individual or agency decision-making process.

Agencies love buzzwords like “synergy”, “ customer-centric”, and “Growth hacking”. But while becoming a buzzword leads to overuse and often reduced meaning over time, that doesn´t change the fact that these terms reach this status because they represent essential concepts to which we all should aspire.

That word is trendy for a reason. But what does it really mean?

A data-driven approach in digital marketing is one that involves the gathering and analysis of data to make informed decisions. But before you can do that, you have to have a system in place that answers some crucial questions key to building a data-driven culture:

  • What kind of decisions do you need to make?
  • How much data do you need to say this is enough to make a decision?
  • What kind of data?
  • Where is this data?
  • How long do you need to collect it and how often?
  • How will you make sense of the data you collect?

 

All of this goes into developing and integrating your data-driven approach. So the role of data in business decisions is to answer questions like:

  • Where to invest your marketing money and time?
  • What messages will resonate?
  • How to increase conversions by using metrics?
  • What type of content to create?

How can data-driven be used in marketing agencies?

There are a number of different types of data that can be used for data-driven marketing, including customer demographics, customer behavior, and marketing campaigns. Marketers need to clearly understand how much and what type of data they need to make informed decisions so their marketing strategies can be successful.

Customer demographics are one type of data that can be used for data-driven marketing. This type of information includes things like age, gender, income level, education level, and geographic location. Digital marketing analytics provides a wide variety of data for eCommerce businesses, and Social Media Analytics will deliver plenty of actionable insights into how a client´s campaigns are performing on various platforms.

Since data-driven marketers apply the use of data to reach a target audience, they assure the creation of personalized experiences and measure the success of their campaign by looking at conversion rates. There are a few tasks you would need to perform to help create a data-driven business process for each of your clients.

The major data-driven activities include:

  1. Customer segmentation: Customer data is based on their behavior, demographics, or other characteristics allows marketers to create targeted messages that are more likely to resonate with each group. For example, tools such as Hubspot, SharpSpring, and Drip, can help with this kind of customer segmentation by creating marketing automation targeted by user behavior.
  2. Campaign tracking and measurement: By tracking the performance of individual marketing efforts, marketing teams identify which formats are most effective and adjust accordingly. This allows them to allocate resources, making the sales team‘s job more efficient. From overall website analytics to specific campaign performance from Google Ads, Facebook Ads, and more, understanding campaign data is critical to being data-driven.
  3. A/B testing: By testing different versions of a campaign or landing page, marketers determine which one is more effective and make changes accordingly.
  4. Personalization: By collecting data about individual customers, marketers create more personalized experiences tailored to each customer´s needs and preferences. This can lead to higher levels of customer satisfaction and loyalty.

 

What are the benefits of a data-driven approach to management?

From improving operations to driving sales, data-driven decision-making offers many advantages. Let´s see how the following examples highlight the many benefits of a data-driven culture in the management of your agency.

  • Better serving customers: Agencies can use data to determine what consumers prefer. For example, in the customer support center, data can help organizations learn the most cost-effective way to address customer questions and issues, reducing problem resolution times and improving customer experiences.
  • Identify new business opportunities: Data can reveal insights that help businesses create additional revenue streams by innovating and developing products and services that meet consumer demands. For example, a retailer of women’s shoes can identify trends that indicate a popular style or brand of shoes. They can then swiftly respond and tailor their products and services accordingly.
  • Grow sales and improve processes: Every business wants to maximize revenue growth. In a competitive global marketplace, data plays a crucial role in identifying and translating data into revenue opportunities. For example, slower sales growth can be a sign of mediocre sales team performance. By digging into the data, a leader can identify problems and develop sales and marketing strategies that can improve performance and grow revenues.
  • Create a First Mover Advantage: Data and analytics can help organizations respond to market changes faster. By harnessing data analytics, businesses can predict future trends, identify consumer behaviors and detect new business opportunities more quickly, creating the potential for obtaining a market advantage.

How can an agency be data-driven?

Just about every business today wants to build a data-driven agency. Pitch decks are stacked full of promises of AI and machine learning, real-time data, and intelligent insights, with companies, investing millions into tools and data initiatives designed to add value in order to appeal to stakeholders.

A data-driven organization is one that embraces a culture of data exploration, has company-wide policies and guardrails in place that ensure accuracy, and provides solutions that both analysts and non-analysts can use to find answers to important business questions. In a data-driven company, everyone is able to make decisions based on reliable, standardized information across many platforms, time zones, and teams.

When data is democratized, everyone can benefit from it without being overwhelmed by manual tasks, being confused about how to interpret it, or the need for a specialized data science skillset. This, and the fact that leadership and employees view data as a critical asset that’s worth investing in, makes an agency data-driven.

What does a data-driven agency look like?

It can be difficult to understand how effective your business is at using data to inform decision-making. One way to asses an agency’s data-driven capabilities is by benchmarking against the Mode data maturity model – take a look at the five stages below to see where are you at.

  • Patchwork analytics: In the first stage, the agency has no official data team. Data analytics is decentralized, with a patchwork of tools and data sources – each department assesses its own data and tries to connect them through exports, spreadsheets, and some integrations. Most analyses are done on historical data, with little to no real-time streaming data sources. Visualizations at this stage, that is to say, the manual nature of data management often leads to errors, inconsistencies, and inaccurate reporting.
    There’s no agency-wide data strategy to enable decision-making, partially because the culture isn’t there. Leadership still leans heavily on instinct over data.
  • Departamental analytics: At this stage, there’s no centralized data team. However, a data analyst might exist in some departments. Data collection is a little more streamlined but analytics is still a silo from team to team, with some departments taking the lead in data maturity or using different tools than others.
  • Reactive analytics: In the third stage, data becomes centralized but still is not accessible to everyone. The company has a data team but their analyses are mainly reactive to data requests from different departments. Internal stakeholders streamline typically a request for reports or dashboards, then wait for the data team to get through a backlog to fulfill it.
    By now the company is likely to have an agency-wide BI tool, along with a data stack that pipes data from different sources into a connected warehouse. They have some data governance in place and are likely working toward self-serve analytics.
    In terms of culture, people think of data mostly as a tool to track performance.
  • Proactive Analytics: At this stage, the agency does have a data-driven culture. Team members proactively seek out opportunities with data, with non-analysts taking it upon themselves to analyze data using self-serve tools. Data team members and business stakeholders collaborate often, predictive analytics are in play, and the culture encourages viewing data as a product rather than a performance-tracking tool.
  • Democratized analytics: The holy grail of data-driven companies, an organization at this stage uses data to inform nearly all decisions. The majority of domain experts are also citizen analysts and are active in ongoing experiments to uncover more value from company data. There´s a clear process for when and how data teams should invest in data applications, and the agency culture is completely intertwined with data – every crucial decision is data-driven.

How to become a data-driven agency?

Before you do anything, it’s a good idea to make sure your team is ready to embrace data at the next stage. You’ll want to have buy-in from your stakeholders on investing in a data analytics solution that works for your agency’s goals and structure. Once you get the go-ahead, it’s time to invest in a platform that can deliver value quickly.

1. Connect your disparate data on one platform

The first step is building a pipeline for your data. Data-driven software was made to bring data sources together quickly-integrate data from each business function, like marketing sales and customer support. Believe it or not, you can build and deploy a complete data stack in just 30 minutes or less, regardless of how big your company is. Once data is connected and analysts can start exploring, you can deliver rapid impact, which can go a long way toward driving cultural change and convincing key stakeholders to trust and utilize data in their daily operations.

2. Establish key metrics to guide the agency’s strategy

To become data-driven, it is recommended for agencies to focus on key analytics-or north star metrics– to separate truth from opinions and make key objectives, and reasoned business decisions. This is more important than focusing on generating revenue or padding the bottom line.

There are some specific conditions that are necessary to make this happen. For example, key metrics need to be singular

“Companies can’t chase dozens of performance indicators, with each team having their own preferred set,” Writes Ben Stancil. “If they do, everyone ends up confused; at worst, people proxy their opinions through weaponized KPIs. This doesn’t end arguments; it escalates them”. Finishes Stancil, an eminence in data-driven solutions.

What’s more, metrics also have to be achievable, and they have to endure. In other words, you shouldn´t be changing key metrics regularly. Instead, as Stancil points out, the metrics you’re optimizing need to point out the spot where you want to be on the horizon.

3. Break down silos and democratize data

To become data-driven, companies must actively work to break down data silos and provide teams with shared definitions and clean data sets. The end goal should be complete data democratization, where everyone in the organization can feel comfortable gleaning insights from different data sources and using them to make better decisions.

4. Make reports easy to read

Most employees today have limited skills when it comes to analyzing and interpreting data. According to a recent Harvard Business article, just 25% of workers feel confident in their data skills. For this reason, it helps to optimize reports by making them visually appealing and easy to read. By doing so, people can explore them with confidence regardless of their skills and experience. Clear visualization makes it easier for nontechnical teams to access and understand data and know how to apply it in everyday scenarios.

Making reports easy to access and use can also help to improve data literacy. The more employees interact with data, the more comfortable they will become using it and relying on it to make decisions.

5. Encourage data-driven meetings

Another great way to become more data-driven is to provide cross-functional, data-driven updates to different teams. Best practices say that organizations should ask their data teams to participate in such initiatives. Including the data, the team enables employees to ask questions to their colleagues who know how to answer them. It also provides additional opportunities for learning and growth.

6. Use interactive data dashboards

Many teams are having success using interactive reports and dashboards that enable employees to access and interact with data in a place that’s secure and user-friendly. For example, dashboards make it easier for your team members to analyze data and iterate, ask questions, and receive answers in one platform.

Becoming data-driven takes time…

Agencies can´t become data-driven from one day to another. It takes substantial resources and buy-in to get from stage 1 to five, but in the long run, it will pay off in dividends.

Benn Stancil explains that being data-driven is a long game and it takes time to accumulate an advantage. Business value comes from putting in the effort of accumulating small wins, which add up over time.

To move toward becoming a truly data-driven company faster, you should choose software and partners that have built into their DNA.

What are the implications of data-driven management?

Data-based decision-making provides agencies with the capabilities to generate real-time insights and predictions to optimize their performance. Through this, they can test the success of different strategies and make informed business decisions for sustainable growth.

There are a wealth of reasons that using data to make decisions is a pursuit every modern business should place at the heart of their culture – and we’re going to explore the main points of importance.

  • Continual organizational growth: The core importance of data in decisions lies in consistency and continual growth. Data-driven decision-making empowers agencies to hone in on key insights based on a multitude of functions, operations, and departmental activities.
    One decision after another actioned with consistency will empower you to set actionable benchmarks that result in continual progress and growth – key ingredients to long-term2 success in today´s cut-throat digital age.
  • Knowledge & innovation: Data-driven business decisions can determine the success of a company, plain and simple. This is a testament to the importance of online data visualization in decision-making.
    MIT Sloan School of Management professors Andrew McAfee and Erik Brynjolfsson once explained in a Wall Street Journal article that they performed a study in conjunction with the MIT Center for Digital Business. In this study, they discovered that among the companies surveyed, the ones that were primarily data-driven benefited from a 4% higher productivity as well as 6% higher profits.
  • New business opportunities: Decision-making based on data leads to the discovery of new and exciting business opportunities. Drilling down into accessible visual information will give you a panoramic view of your business’s core activities, which in turn, will ensure you make a series of solid decisions that benefit the commercial evolution of your business.
    Armed with the deep-dive insights that will improve your judgment, you will uncover opportunities to expand your growth, create new professional connections, and develop innovations that will give you an all-important edge over the competition.
  • Better communication: Working with a data-driven decision management mindset, you will become a better leader- and that will filter down throughout the entire agency.
    Whether you’re talking data-driven finance, a data-driven sales strategy, or any other kind of insight-driven initiative, working with powerful KPIs and visualizations will improve communication across the board.
    Operating as one cohesive data-driven unit, every one of your departments will gain the ability to share insights with ease and collaborate on key strategies that will ultimately turn you into a more intelligent and profitable business.
  • Unrivaled Adaptability: Last but certainly not least, one of the prime benefits of data-driven decision-making is that it will drive your business to be incredibly adaptable.
    By embracing digital data, you stand to grow and evolve your empire over time, making your organization more adaptable as a result. The digital world is in a constant state of flux, and to move with the ever-changing landscape around you, you must leverage data to make more informed and powerful business decisions.
    Data-driven decision-making tools will allow you to connect with emerging trends and patterns that concern not only your internal activities but the industry around you. If you can understand these trends or patterns on a deeper level, you can make informed decisions that will ensure you remain competitive, relevant and profitable at all times.

What is the role of data in data-driven management?

  • Improves people’s lives: Data will improve the quality of life for the people you support. improving quality is first and foremost among the reasons why organizations should be using data. By allowing you to measure and take action, an effective data system can enable your agency to improve the quality of people’s lives.
  • Make Informed decisions: Data = Knowledge. Good data provides indisputable evidence, while anecdotal evidence, assumptions, or abstract observation might lead to wasted resources due to taking actions based on an incorrect conclusion.
  • Avoid small problems from turning into a major crisis: Data allows you to monitor the health of important systems in your organization: By utilizing data for quality monitoring, organizations are able to respond to challenges before they become full-blown crisis effective quality monitoring will allow your agency to be proactive rather than reactive and will support the organization to maintain best practices over time.
  • Get the results you want: Data allows agencies to measure the effectiveness of a given strategy: When strategies are put into place to overcome a challenge, collecting data will allow you to determine how well your solution is performing and whether or not your approach needs to be tweaked or changed over the long term.
  • Find solutions to problems: Data allow agencies to determine the cause of problems. It allows visualizing relationships between what is happening in different locations, departments, and systems. If the number of medication errors has gone up, is there an issue such as staff turnover or vacancy rates that may suggest a cause? Looking at these data points side by side allows us to develop more accurate theories, and put into place more effective solutions.
  • Back your arguments: Data is a key component of systems advocacy. Utilizing data will help present a strong argument for systems change. Whether you are advocating for increased funding from public or private sources or making the case for changes in regulation, illustrating your argument through the use of data will allow you to demonstrate why changes are needed.
  • Stop guessing: Data will help you explain decisions to your stakeholders. Whether or not your strategies and decisions have the outcome you anticipated, you can be confident that you developed your approach based not upon guesses, but solid data.
  • Be strategic in your approaches: Data increases efficiency. Effective data collection and analysis will allow you to direct scarce sources where they are most needed. If an increase in significant incidents is noted in a particular service area, this data can be dissected further to determine whether the increase is widespread or isolated to a particular site. If the issue is isolated, training, staffing, or other resources can be deployed precisely where they are needed, as opposed to system-wide. data will also support agencies to determine which areas should take priority over others.
  • Know what you are doing well: Data allows you to replicate areas of strength across your agency. Data analysis will support you to identify high-performing programs, service areas, and people. Once you identify your high performers, you can study them in order to develop strategies to assist programs, service areas, and people that are low performing.
  • Keep track of it all: Good data allows agencies to establish baselines, benchmarks, and goals to keep moving forward. Because data allows you to measure, you will be able to establish performance goals. A baseline is what a certain area looks like before a particular solution is implemented. Benchmarks establish where others are in a similar demographic. Collecting data will allow your organization to set goals for performance and celebrate your success when they are achieved.

Conclusion

We´ve explored several compelling examples of data-driven decision-making, and there is no point in denying it – by harnessing data in the right way and measuring your success, you stand to propel your business to new and exciting heights.

Having access to all key ingredients and knowing the benefits of data-driven management, it’s time to put your plans into action. Remember for maximum success, you must avoid taking the wrong approach to data-driven business decisions at all costs. A failure to do so will lead to making choices with a gut instinct and biases or fostering poor data culture within your agency. Combine the very best software with a cutting-edge perspective toward evaluating your decisions to start seeing results.

 

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