Here on The Pipeline, we regularly cover topics related to business data and business data management. In fact, there are very few aspects of business data we have yet to cover.
But, today we’re venturing into uncharted territory to discuss a recent—and necessary—trend in business data. That is, the switch from static to dynamic data management.
Today’s blog post explores the difference between static and dynamic data. We also look at why this transition is critical to the success of the modern business. Let’s get into it.
Dynamic Data vs. Static Data
As you may have guessed, static data refers to a fixed data set—or, data that remains the same after it’s collected. Dynamic data, on the other hand, continually changes after it’s recorded in order to maintain its integrity.
In concept, the difference between static and dynamic data is simple enough to understand. Yet, when you look at the impact data has on the average business, things become slightly more complicated. Here’s what we mean: In the past, organizations mainly relied on static data to conduct sales, marketing, and operations.
But, as technology increased the efficiency of businesses everywhere, companies began to collect data faster. Meanwhile, the data they’d collected began to decay at an unprecedented pace. In fact, in 2014 we reported that a staggering 94% of businesses believed their prospect and customer data to be inaccurate (source).
In recent years it’s become abundantly clear that the world of customer and prospect data must undergo a transformation. And luckily, we’re seeing more businesses make the shift to a more dynamic mindset when it comes to data.
4 Reasons to Make the Shift to Dynamic Data Management
Although the concept of dynamic data seems simple enough, making static data more dynamic often seems like a daunting task. Because many businesses aren’t sure how to start the process of data cleanup and diligent data management, they simply don’t do it.
If this sounds like your business, your static data might be hurting you more than you think. Consider these statistics:
- 40% of business objectives fail due to inaccurate data (source).
- Bad data costs U.S. businesses more than $611 billion each year. (source)
- 64% of “very successful” data-driven marketers say improving data quality is the most challenging obstacle to achieving success (source).
There’s no way around it, static data is a modern-day death sentence to the success of any organization. Although that alone should be enough to convince you to make the switch to dynamic data management, here are four more compelling reasons you can’t afford to ignore this massive shift in the world of business data:
1. Dynamic data enables a customer-centric business strategy across all departments.
Today’s customers are well-informed. They know what they want—and they’re calling the shots. In the current, hyper-competitive market, if a customer’s needs aren’t met, they simply take their business elsewhere—to a brand that will deliver a more positive experience. In fact, 91%of customers who have a bad experience with an organization won’t be willing do business with that company again (source).
Although most modern companies recognize the importance of a customer-centric business model, many aren’t aware of the vital role dynamic data plays in achieving true customer-centricity. Think about it this way: In order to thoroughly understand your customers and offer experiences that speak to their wants, needs, and preferences, you need access to prospect and customer data.
Now, if the data you have is static, it starts to decay the moment you collect it—after all, people themselves aren’t static. We start new jobs, move to different cities, and we change our minds about things all the time. Static data doesn’t account for these changes. But, dynamic data does—updating in real time as these changes occur.
With dynamic data, you can confidently analyze your customer base and create personalized experiences to ultimately increase customer lifetime value and reduce churn. For a more in-depth look at personalized marketing and customer-centric business strategies, we recommend the following articles:
- B2B Guide to Marketing Personalization
- Role of Personalization in B2B Sales
2. Progressive persona profiling.
Here at ZoomInfo we talk a lot about buyer personas—what they are, why you need them, and how to create them. But, what we have failed to acknowledge is that, although useful, the standard buyer persona is static—unlike real human beings.
To bring buyer personas up to speed and make them more dynamic, the KERN Agency came up with something called progressive persona profiling. Progressive persona profiling is a concept similar to the process of creating traditional buyer personas. However, this model also takes the fluid nature of human behavior and decision-making into account.
Scott Levine, VP of the KERN Agency, explains the thought process behind progressive persona profiling like this:
“Progressive persona profiling is based on the rapidly changing human behavior patterns that occurred as a result of the convergence of faster connection speeds on both mobile and home devices, the accelerated adoption of online searching and sharing, and the proliferation of social networks and always-on communication abilities.”
Progressive persona profiling is the logical next step in persona creation, as it’s a more dynamic approach to an age-old marketing practice. But, in order to use progressive persona profiles to your advantage, you need access to one thing. You guessed it—dynamic data.
Dynamic customer and prospect data will fuel your progressive persona profiles and ensure they evolve alongside the actual prospects you’re trying to reach.
3. Dynamic data facilitates better business-wide communication and alignment.
Static data is often kept in separate silos and left to decay at the hands of the departments who need access to it. Dynamic data on the other hand is shared freely between departments and platforms—as it’s continuously updated and stored in a centralized location.
This means, an entire organization has access to identical information regarding customers and prospects. If a data set is truly dynamic, it takes less effort to achieve consistency across sales, marketing, branding, and more.
For more information about the importance of open communication and alignment, check out the following resources:
- 3 Sales and Marketing Alignment Best Practices
- Swim Lanes for Marketing, Sales Development, and Sales
- 20 Sales and Marketing Alignment Statistics
- How to Improve Communication Between Marketing and Sales
4. Dynamic data is hygienic data.
When we refer to dirty or bad data, we are referring to data that is out-of-date, incomplete, or incorrect in some capacity. Although no data set will ever be 100% accurate, implementing a more dynamic approach to data collection and data maintenance will significantly improve the quality of your data.
Hygienic data is critical to all essential business processes. This includes the operation of key business technology, sales prospecting, reporting, selling, marketing and so much more. Research even shows that inaccurate data has a direct impact on the bottom line of 88% of companies, with the average company losing 12% of its revenue as a result (source).
Simply put, businesses can no longer rely on static data. Saying, “I don’t care if my data isn’t dynamic,” is the same as saying, “I don’t mind losing a significant portion of my revenue.”
Final Thoughts on Making the Switch from Static to Dynamic Data
The main takeaway here is obvious: Dynamic data is critical to success in the current business landscape. Yet, the one question we’ve left you with is, “How do I transform static data to dynamic data?”
Although there is no single answer to this question, we’ll leave you with our best advice. Invest in your B2B data and trust the professionals to handle it. Recent technological advancements have enabled companies like ZoomInfo to release groundbreaking tools and services. These tools and services give businesses exclusive access the most dynamic data set on the market.
In addition to our extensive business database of direct dial phone numbers and email addresses, our platform has the unique ability to automate critical data maintenance processes, alert you to important changes in your data, and regularly deliver timely updates about the contacts and companies you care about most.
For more information about making the shift from static to dynamic data, click the banner below. Our team of data professionals can work with you to grow your business and improve your data today.
Flexibility: Dynamic data structures can grow or shrink at runtime as needed, allowing them to adapt to changing data requirements. This flexibility makes them well-suited for situations where the size of the data is not known in advance or is likely to change over time.Why is dynamic data important? ›
In data management, dynamic data or transactional data is information that is periodically updated, meaning it changes asynchronously over time as new information becomes available. The concept is important in data management, since the time scale of the data determines how it is processed and stored.What is the difference between static data and dynamic data? ›
Dynamic Data vs. Static Data. As you may have guessed, static data refers to a fixed data set—or, data that remains the same after it's collected. Dynamic data, on the other hand, continually changes after it's recorded in order to maintain its integrity.What are the benefits of making data dynamic for everyday users within business? ›
With dynamic data, you can be sure that all the decision-making processes are made in accordance with the latest available knowledge, which helps to conduct business operations much more efficiently. An example of dynamic data is the Google Analytics tool which offers you up-to-date insights into the website traffic.What are the pros and cons of static data structures? ›
Advantage: The memory allocation is fixed and so there will be no problem with adding and removing data items. Disadvantage: Can be very inefficient as the memory for the data structure has been set aside regardless of whether it is needed or not whilst the program is executing.What are the disadvantages of static data structure? ›
The following are the disadvantages of Static Data Structures: We have to evaluate the maximum amount of space that is needed to store the element in memory. We cannot reallocate extra space in memory, once the Static Data Structure is initialized with a fixed size in the memory. A lot of space might get wasted.What are the disadvantages of dynamic data structure? ›
One of the major drawbacks of the dynamic data structure is the issue with memory consumption. As we know the amount of memory that needs to be allocated to the data structure is not fixed in the case of dynamic data structure there is always a potential chance of memory overflow by the data structure.What is the difference between static and dynamic implementation? ›
Static data structures are of fixed size and memory is allocated at the compile time by the compiler and deallocates when they go out of scope or program ends. Dynamic data structures are of dynamic size and memory is allocated at the runtime for them by the program.What are good reasons to use dynamic attributes? ›
Dynamic attributes enable you to add attributes to your model, and to create custom logic for them, without touching the model class itself. They provide a way to generate new data, and access it without calling a separate service to do so. Dynamic attributes are transient data that is not persisted to the database.Is it better to work with static or dynamic data types? ›
Conclusion. In this article, we reviewed data types, type checking, and the two main techniques used for type checking in programming. Dynamically typed languages offer more flexibility, but with less optimised code, while statically typed languages offer more optimised code with less flexibility.
In general, statics is focused on understanding the forces acting on a body that is not moving or is moving very slowly, while dynamics is focused on understanding the forces acting on a body that is moving at a significant speed.What is an example of static and dynamic data? ›
An example of static data, is a newspaper, as once it has been printed, the information on it cannot be updated, whereas an example of dynamic data, would be a website, as that can be updated as and when needed.Why do companies want user data? ›
Businesses may collect consumer data and use it to power better customer experiences and marketing strategies. They may also sell this data for revenue.Why do we need a dynamic business environment? ›
Since the environment is inherently dynamic in nature, it constantly keeps changing. This keeps the managers motivated to continuously update their knowledge and skills. This helps them prepare for predicted and unpredicted changes in the realm of business.Is being dynamic is important in business? ›
Dynamic business strategies help to ensure that a business can respond appropriately to changes that may represent both potential opportunities and new threats to its operations.What are the advantages of dynamic memory over static memory? ›
Dynamic memory is not fixed and can be reused and changed for different applications. Static memory is fixed and hence cannot be reused for different applications. Memory can be allocated or changed at any point in time. Allocation of memory is permanent and cannot be changed.Why is dynamic allocation better than static? ›
Generally, static memory allocation is best for simple and small programs, or for variables and data structures with a fixed and known size and lifetime. Conversely, dynamic memory allocation is better for complex and large programs, or for variables and data structures with a variable and unknown size and lifetime.What are two differences between a dynamic data structure and a static data structure? ›
A static data structure is one that has a fixed size and cannot change at run time A dynamic list is able to adapt to accommodate the data inside it and so it does not waste as much space.What are the advantages of dynamic methods? ›
- This allows for polymorphism. ...
- It helps us to reuse the code because of method overriding.
- It makes our code more flexible. ...
- It allows us to define abstract methods in a superclass and implement them in subclasses.