The volume of data coming into company systems keeps increasing every year and, according to some estimates, 7.5 septillion gigabytes of data are created every day. However, simply collecting all of this data is not enough. It needs to be refined to extract the needed business insights.
As well as raw data not being enough, there exists a huge problem with “dirty data” such as duplicates and inaccuracies, that may be costing companies as much as 12% of their overall revenue.
In this post, I will share some data hygiene best practices that you should implement to maintain high quality data that will increase revenue and overall return on investment from Salesforce.
What is Data Hygiene?
In order to make more accurate business decisions, you need to work with structured data. This means accurate, consistent, and complete information. Such data is considered to be hygienic or cleansed and it can be further enriched to extract business insights. One of the most common misconceptions out there is that data cleansing is simply about deleting or replacing outdated information to make room for fresh data, but this barely scrapes the surface of proper data hygiene. The goal is to create standardized and uniform data sets that can be used by various analytical tools.
The benefits of data hygiene include:
- Increased customer acquisition – Hygienic data allows companies to create more accurate prospect lists. This increases the effectiveness of your marketing team since you are targeting the right people and leads to higher engagement rates.
- Better decision making – All business decisions need to be based on solid data. Without proper data hygiene, you could be getting an erroneous picture of your customer. This makes it very difficult to address their needs and concerns.
- Optimized employee productivity – One of the negative results of poor data hygiene is that your employees waste time pursuing unqualified leads. Conversely, clean data provides a better picture of whether a prospect has potential and thus reduces the amount of time that is required to convert or discard in favour of moving on to a more suitable prospect.
Now that we understand what data hygiene is and the benefits it has to offer, let’s take a look at some of the data hygiene practices you need to be performing on a daily basis.
Conduct a Data Audit
Before jumping head-first into fixing any issues that you are experiencing with your data, it helps to understand the scale and magnitude of these problems. Research from IBM shows that 27% of business leaders do not know the accuracy of their data. So before deciding on any action, you need to get an overall idea of just how serious the problem is and establish a realistic baseline for the company’s data hygiene.
Take a close look at all of the in-house systems that your company relies on for accurate customer information. This will typically be your CRM and various databases used to store raw data.
Next, identify the critical input streams into those repositories, since too much information is a significant contributing factor to bad data. Even though most companies want to amass as much information about their customers as they can, more is not always better. If you are collecting information that will not help you convert leads, then there is no reason to keep it.
In addition to auditing internal systems, you should also take a look at other data sources. This includes things like gated content including e-books, webinars, and whitepapers. Make sure that you are only collecting relevant information. If you have too many input fields, customers will just input random data in order to access the content.
Deduping Your Data
Deduping data is one of the core aspects of data cleansing. This includes identifying and removing exact duplicates and fuzzy duplicates. For most companies, this process can be challenging because they have all kinds of ongoing sales and marketing activities with many stakeholders and campaigns. The result is a double whammy of bad data because the existing data contains duplicates and the new data coming in will likely contain duplicates as well. Therefore, you need to implement a comprehensive approach that addresses the duplicate issue in all of its shapes, sizes, and input streams.
The best way to do this is to use tools that leverage machine learning. For example, let’s say you have 250,000 records and you would like to check how many of them are duplicates. It would not be efficient to create and maintain rules inside Salesforce that cover every single scenario. By using machine learning algorithms you can let computers construct rules that identify future duplicates based on past deduplication activities.
Perform Automatic Data Cleansing
It is important that such processes are done automatically since deduping thousands and thousands of records is simply impractical. Errors can be introduced easily and even one spelling mistake can cause a lot of confusion. This ties into the issue with duplicates mentioned above.
For example, companies often use simple guidelines to distinguish between duplicate and non-duplicate contact entities, such as an email address. You can easily end up in a situation where a customer enters their work email when filling out one form and then enters their personal email when filling out another form. The result is two separate records and both contain critical information, but you will never detect that they are duplicates by using the email address. Systems that perform data cleansing typically use many rules for merging and removing duplicates which is why they are key to proper data hygiene.
Eliminate Organizational Silos
Even though marketing and sales teams usually work hand in hand, they often rely on different systems to get their work done. Sales teams typically rely on the CRM and marketing works with various automation platforms. The result is that these two teams have their own data standards and formats. Therefore, it is very important that everybody that updates customer information must follow the same standards for inputting and updating.
Some companies try to mandate a central customer intelligence platform where employees are restricted in what they can do. This is an option, but if it is too restrictive employees just avoid using it and turn to their own homegrown approaches like spreadsheets.
The ideal approach would be to integrate the disparate databases into one repository. If your organization is using Salesforce as your CRM, you can turn to one of their products called MuleSoft. It is one of the most popular integration platforms in the world and you will be able to connect systems both on-premise and in the cloud. Mulesoft offers a Salesforce connector that will allow you to accelerate Salesforce integration and it gives you access to all Salesforce entities to enable automation for your business processes.
Frequently Update Your Data
In some ways, the customer data that you have in your CRM is like groceries that you buy at the supermarket. There are many options to choose from but you need to select the one that is the best for you. More importantly, groceries have an expiration date, and so does your customer information. Customers and prospects will change offices, get new email addresses and their business needs will evolve over time. You need to stay on top of all these changes to avoid data decay.
For example, every year, as many as 18% of all telephone numbers change, and the percentage is even higher for executives at 21%. Assuming that B2B data expires at a rate of 70% each year, you are sending out the wrong message to the wrong person 7 out of 10 times, unless you refresh that information regularly.
Start Using Machine Powered Tools to Boost Your Data Cleansing Hygiene
There are lots of tools available on the Salesforce AppExchange that will help you along on your data cleansing journey. If you are a Salesforce administrator, we would recommend checking out some of the tools that will make your role a lot easier. Machine learning offers us a much faster and accurate way of boosting the quality of your data, enabling you to extract more insights and gain a complete 360 view of your customer.
Companies looking to dedupe Salesforce are using machine learning to get the job done quickly and efficiently, but it’s important to note that this approach needs to be applied to all stages of the data cleansing process.
Cleaning your data gets more and more expensive the longer it persists in your system. As a rule of thumb, you should follow the 1-10-100 rule. It costs $1 to verify if a record is correct, $10 to fix it, and $100 if nothing is done about it. As you can imagine, the costs of bad data can snowball quickly, which is why it is better to be proactive and practice quality data hygiene.