In a world where data drives our marketing, sales, and customer success initiatives, bad data has increasingly become a problem for companies of all sizes. Right now, your company is missing out on revenue because of bad data in your HubSpot databases. That’s right. It’s a fact of life for any company that collects and uses even moderate amounts of customer data.
A data entry error might keep a marketing email from being delivered to a prospect that would have ultimately responded well and become a long-term customer. Maybe a data capture error kept vital information about a prospect from a sales rep, causing them to underperform during a sales call. Or, maybe you’ve wasted valuable time sending marketing materials to leads with outdated records, causing you to sink a significant portion of your budget with nothing to show for it. There are an unending number of ways that bad business data can have a negative impact.
Often, a small bad data-related incident like the ones described will spark a deeper investigation into how bad data is affecting a company in other ways. Almost always, asking those questions leads to companies determining that the impact is more substantial than they had initially suspected, and is actually a driving force behind many missed opportunities.
Here are a few statistics that show just how serious the problem is:
- A study from The Data Warehousing Institute found that poor data costs U.S. companies more than $600 billion per year.
- In another study, IBM found that data problems could be costing U.S. companies as much as $3.1 trillion per year in 2016. The figure received a lot of attention when the study first came out.
- 30% of companies have no plan in place to update or rectify bad data.
- Types of data quality issues based on a survey with more than 1,900 respondents conducted by O’Reilly.
In a rush to provide marketing messages that are more personalized, many companies have placed too much focus on collecting more data without enough thought into ensuring the integrity of the data in their HubSpot account. Today 33% of companies have more than 100,000 records in their database. But most companies believe up to 25% of their data may be inaccurate.
Bad HubSpot data doesn’t always just lead to a single missed opportunity — it can have a cascading negative effect throughout a company. Bad email data entry practices, for instance, could lead to more bounced emails and impact the whole company’s reputation among email providers.
Let’s take a look at exactly at how low-quality data harms your marketing efforts:
- How Does Dirty Data End Up In Your HubSpot Marketing Database?
- 3 Ways Bad Data Hurts Your Marketing
- Steps Companies Can Take to Protect Themselves
- Clean, Quality Data Drives Better Results
How Does Dirty Data End Up In Your HubSpot Marketing Database?
One of the biggest surprises that companies have when they start digging into their HubSpot data is the sheer volume of bad and inaccurate data in the average database. When you collect data, you do so with the best intentions. It’s not that hard for a prospect (or your team) to enter their information correctly...right? That would be nice. But the truth is that any data collection program that requires any manual human input is going to experience data entry errors.
But dirty data comes from a wide range of mistakes, issues, and data collection errors. To understand how dirty data ends up in your HubSpot marketing database, you have to understand all of the different ways that it can happen.
Bad data can come from a wide range of sources, including:
- Missing data.
- Manually-entered inaccuracies.
- Data that’s been entered in the wrong field.
- Data formatting issues.
- Duplicate data.
- Errors during import or export.
- Versioning mistakes.
- Misspells, typos, and other errors.
No matter where your bad data comes from, it can have a significant impact on the success of your marketing campaigns. Let’s take a look at the three biggest reasons all companies should consider instituting data integrity and quality assurance programs.
3 Ways Bad Data Hurts Your Marketing
There are many ways that bad data can harm your marketing and sales campaigns. Sometimes this impact will be specific to your own campaigns. But there are some ways in which low-quality data commonly impacts campaigns.
These are some of the driving reasons why studies have shown colossal figures in the billions (or even trillions) in losses caused by bad data practices.
1. Low-Quality Data Makes Lead Scoring Difficult
Lead scoring is at the center of some of the most successful B2B marketing campaigns. Knowing where to focus your attention and identify what stage of the buying process individual leads are in is critical for optimization. However, 79% of B2B marketers have not established lead scoring within their marketing operations.
Lead scoring relies heavily on your ability to collect accurate data from prospects. You need to collect enough data to gain a complete picture of each prospect to score them accurately. You can’t use what you don’t collect. In the effort to scale the data that you collect, make sure that you don’t sacrifice data quality in your HubSpot databases.
Duplicate HubSpot records can make lead scoring difficult. Sometimes, the same lead will get scored twice and receive two completely different scores. Then, when a salesperson is assigned that lead, their approach will be dictated by which record they had assigned to them. Beyond that, the wrong record might receive updates. This can make it difficult to track and identify relevant companies in your HubSpot database and result in lost sales.
Errors in your data mean errors in the scores that you assign to leads and accounts. What if a company’s estimated annual revenue was incorrectly entered as a substantially lower amount in your HubSpot companies database? All associated leads with that company would then have incorrect scores, due to the lower revenue opportunity.
It’s impossible to quantify the cost of missing out on these leads without a full data quality audit. Even then, data quality requires consistent efforts to maintain. Investing in data quality assurance for your HubSpot data means drawing attention from your teams, investing in tools, and working to improve how you collect that data.
Poor data quality that results in lead scoring mistakes leads to inaccurate time management for your sales teams and marketing teams. They’ll focus on the wrong leads. They’ll spend time preparing based on inaccurate data. They’ll have less confidence in the lead data that they do receive and will spend more time on their own research.
2. Deep Personalization Requires Confidence in Your Data
Personalization has never been more important than it is today and its usage will only grow as time goes on. Companies are working toward deeper, more data-rich personalization based on the actions that their customers take all the time. HubSpot builds deep personalization into all of their features, allowing you to speak directly and specifically to your customers about their problems and needs.
It’s become so prevalent that modern customers expect it. 78% of customers will only engage offers if they have been personalized based on their previous engagements with a company. Customers have become increasingly annoyed with traditional non-personalized messaging.
There is no question that personalization is effective. But for the type of true, deep personalization that many companies are looking for and HubSpot is able to provide, they need to have a wealth of data.
With that data, there needs to be a certain level of confidence. The only thing worse than not using personalization in HubSpot marketing campaigns is doing it and getting it wrong. Without confidence in your data, you can’t leverage opportunities to inject data into your campaigns.
Without accurate data that you have confidence in, you’ll have a hard time designing fully formed personalization campaigns that reach their potential.
3. Inaccurate Marketing Data Negatively Impacts Brand Perception
Inaccurate marketing data doesn’t just affect your bottom line, it also negatively impacts the perception of your brand. Imagine being shown marketing that has been “personalized” but uses inaccurate data. Maybe an email calls you by the wrong name. Or worse, calls you “[firstname].” They could address you by the wrong job title, or say that you work for the wrong company. Wouldn’t that affect your opinion of the brand?
Those early impressions of your brand stick. Once a customer develops a negative opinion of your brand, 70% of customers will avoid buying your products.
When prospects receive ads that incorrectly use personalization data or fail to deliver their message in a way that resonates, it can be a frustrating experience for customers. Additionally, dirty HubSpot CRM data can cause sales reps to reach out to prospects using inaccurate data to drive their engagements, derailing conversations and killing conversion rates. The impact of bad data flows throughout an organization. It’s never isolated to a single campaign or issue.
Steps Companies Can Take to Protect Themselves
Bad CRM data can seriously impede your marketing and sales campaigns. Luckily, companies with dirty data aren’t stuck forever. There are steps that you can take to rectify your current data quality problems and put yourself in a position to mitigate them moving forward. These steps include:
- Launch a comprehensive HubSpot data audit. You can make all of the changes to your processes that you want to avoid future data quality issues, but you have to start by identifying and fixing current issues with your HubSpot CRM data. Using a tool like Insycle’s Data Health Assessment that surfaces 30+ common types of issues in your customer data can give you a clean slate moving forward.
- Make proper data collection a priority. Take steps to ensure that when you collect data, you are collecting it the right way. This is especially true for any manually entered data — whether it is from customers or your own internal teams. Make sure that different form fields have the correct input formatting requirements, or are automatically checked for accuracy before inclusion in your HubSpot CRM.
- Schedule regular & ongoing data maintenance. Where there is data, there is a variance in the quality of that data. You will always have to maintain your data, make sure that you have the solutions and processes in place that facilitate ongoing improvement in your data quality. Insycle is a HubSpot customer data management solution that offers in-depth HubSpot data automation features that not only allow you to clean your database in a variety of ways, but schedule those same tasks to run automatically on a recurring basis. The system provides true data cleansing automation, ensuring that you always have a database with few errors and accurate data that you can rely on.
- Use software solutions to reduce manual editing and input. Human error is one of the biggest drivers of poor data quality. HubSpot offers numerous ways to streamline and automate data collection and reduce human error in manually entered data. Reduce and limit the amount of manual input from your customers and teams wherever you can. When it is unavoidable, use software solutions to help ensure conformity, catch duplicates, and identify other issues.
By following these best practices, you put yourself in position to protect your data, improve data quality going forward, and ensure that you have confidence in your CRM data.
Clean, Quality Data Drives Better Results
High-quality HubSpot CRM data drives alignment between your marketing, sales, and customer success teams. It helps to achieve a single customer view, where all teams are working with the same, accurate records to drive their tactics and initiatives.
Clean data allows you to improve lead scoring so that your team can focus on engagements with higher value accounts. That data enables you to improve your personalization efforts throughout your campaigns.
However, inaccurate marketing data can have a negative effect on how customers perceive your brand.
Looking to grow better? Improving your data quality might be a good place to start.