Michael Epps Utley 
Are you finding it challenging to sift through marketing and sales data?
It’s a common issue for small business owners and marketers, and it’s entirely understandable considering the volume of data available today and the constant advancements in the systems and software that deliver it.
This article reveals five common challenges small business owners face related to marketing and sales data and tips for overcoming them.
Challenge 1: Data Availability
Despite all the data being generated today, you may find data gaps. Common gaps include:
Lack of attribution
Incomplete contact information
Not all marketing and sales activities are tracked
These data holes are not always the result of absolute data unavailability. They are more often caused by marketing and sales teams' lack of process—or failure to follow process. This is a missed opportunity because a lack of data tracking means that metrics cannot be reported.
The good news is that this is one of the most straightforward data challenges to overcome.
Resolving the Challenge of Data Availability
Start by reviewing how you track marketing and sales data (if there is an error in tracking, find out why and resolve the issue). If you don’t have a process, it’s worth developing one.
Start by identifying the marketing and sales data you want to track
Figure out which systems and software could best track and report on the data
Identify who is responsible for inputting information (for example, the results of sales calls) or whether data is automatically collected (website and social media clicks)
Identify who should monitor different metrics, how often they should be checked, and what to look for
Figure out who should compile reporting and recommendations and who needs to be on the reporting distribution list
Determine who should act on recommendations and the timeframe
Set a schedule for reviewing your data-gathering and reporting process (it shouldn’t be once-and-done because of the fast evolution of data tracking today)
Lastly, determine the consequences of not following the process you define. Without a strong process and proper training, marketers, salespeople, and even small business leaders will likely backslide, resulting in continuing data gaps.
Challenge 2: Lack of Data Integration
Because of factors unique to small businesses (including limited budgets and lack of tech expertise), many have to depend on outdated sales and marketing systems. Integration issues abound when this is the case. This often makes it challenging to access data and (even when you can find it) figure out how it all fits together.
The only solution to this is to make it a priority to integrate data across systems. This will provide a more complete view of a customer or prospect, connecting activity throughout the buying journey. It will help you better align and refine your sales and marketing efforts.
Resolving the Data Integration Challenge
Begin breaking down your data “silos” by coming up with a list of data collection processes and tools, including your CRM, marketing automation, and analytics systems. Once you have the list, you can determine if any of the solutions can be linked.
Many analytics tools offer integration capabilities with other platforms. Or, you could have a tool you use for one function that could be leveraged for others. If you find gaps in your ability to connect systems, it could be time to explore new options. Even if your budget is limited, investing in integrated marketing and sales technology could pay off by providing the metrics you need to improve your business results significantly.
Challenge 3: Data Too Big to Analyze
Anyone who has tried to analyze thousands of rows across multiple columns of marketing data in a spreadsheet knows it's cumbersome and time-consuming. The volume of numbers has grown more quickly over time than the average human ability to analyze them.
The good news is that artificial intelligence can help you sort through massive amounts of data and generate insights.
Resolving the Challenge of Big Data
Upload your spreadsheets to an AI-based analysis tool. In a short time (sometimes seconds), it can sort through large volumes of numbers and come up with insights to help improve your content, social media, email, and other marketing efforts. Make sure the data you upload is clean and valid. The information you receive through an AI analysis tool is only as good as the data you input.
Challenge 4: Bad Data Woes
“Is my data accurate?”
It’s a common question asked by small business owners who aren’t metrics experts.
This trust gap is typically the result of a lack of transparency regarding the sources of data. For example, the fine print that appears when you search for information about data presented in Google Analytics may leave you questioning whether the numbers reported are accurate.
Resolving the Challenge of Data Quality
Unfortunately, the only way to resolve your data trust issues is by doing your homework. Before signing up for a new tool that delivers marketing data, you must read the documentation or ask the rep questions. Focus on:
Data quality. How can you feel confident the tool delivers quality data?
Effectiveness. Is the data analysis supplied valuable and accurate?
Integrity: Is the data sourced, used, and distributed in acceptable and ethical ways?
Resilience: Will the tool be able to generate quality data long into the future?
If you work through these issues with all your data generation and analysis tools, you should be able to overcome your concerns about whether your data is good.
Challenge 5: You’re Unable to Make the Predictive Leap
Leveraging data to improve past marketing and communication efforts is good. Using it to figure out what customers and prospects will want in the future is even more powerful.
More than likely, you guess what people need and want based on things that have already happened. However, you probably haven’t made the predictive leap to uncover deeper trends that could require your business to change — maybe significantly — to get ahead of consumer demand.
Resolving the Challenge of Predicting the Future
Consider how artificial intelligence coupled with machine learning (ML) could help you predict future challenges and opportunities. ML and AI technologies not only automate data analysis but can also create models using your multi-channel data to determine what is likely to happen if you continue the status quo or make changes to your business.
Because of their novelty, AI and ML solutions may seem challenging to implement for many small business owners. The good news is that you can start slow and learn as you go.
Overcome Your Data and Analytics Challenges in 2025
The importance of data and analytics will continue to increase as we enter 2025 and move beyond. With the right people, processes, tools, and technologies, you can overcome your data challenges and evolve your small business into a confident data and analytics powerhouse.
