Data is the bread and butter of almost every B2B company. It may make perfect sense that the more data a company has, the better off it’ll be.
It isn’t quite true. More data is not necessarily better, and it depends heavily on the quality and accuracy of the collected data. This is where data enrichment comes in.
What is data enrichment?
Data enrichment is the process of taking raw data and making it more accurate and reliable.
You can do it by adding new records to increase the size of the dataset or verifying data accuracy through a third company — these provide important safeguards for companies against events such as the loss of data due to outdated and redundant entries.
For example, imagine you have a data set that includes 2000 records. Some of these records will prove very valuable, while others are worthless. To understand the value of the dataset as a whole, you have to sort through each record to salvage useful data and discard the rest.
This is data enrichment in a nutshell. This powerful data can then be used to segment audiences, add new insights, and build account-based marketing campaigns.
Data enrichment vs. data cleansing?
Although the terms are interchangeable, data enrichment and data cleansing are different.
Data cleansing is the act of removing inaccurate or old data from datasets, while data enriching focuses on enhancing existing data in different ways.
Data cleansing ensures your data is correct and high-quality, while data enriching enhances it.
The benefits of data enrichment
Data enrichment gives businesses access to more accurate data. Decisions based on this data will also be more precise and likely correct. It also saves from potential embarrassment.
Your sales team will always be up to date on the most accurate data they can find, thanks to high-quality data through data enrichment.
Additionally, data enrichment can highlight certain trends in data to show you opportunities that you may otherwise have missed. For example, learning that a prospect was already acquired by a current client — saving you time that you may have wasted attempting to pursue this lead.
Top 5 data enrichment strategies
Now that we’ve covered some benefits of data enrichment, let’s dive into some of the best strategies to enrich your data.
Web scraping is what it sounds like — scraping large amounts of data from the web to enrich your B2B database.
One of the best parts about web scraping is it’s very affordable since the data is freely available. You can import it straight into a CRM or spreadsheet.
Besides being an affordable way to beef up your database, scraping is also relatively simple. Even non-programmers can do it without having to write scripts — just use a tool such as Captain Data to extract data from websites automatically.
Web scraping also gives you total flexibility when choosing which data to extract. Set up an automated workflow to keep running in the background. Soon enough, your team should have ample data to work with.
However, users of web scraping should be aware that not all of the information on the web is accurate. For example, you need to validate scraped data before being used in outreach campaigns via email validation tools.
A second option for data enrichment comes through manual research. It includes looking up leads on information-heavy websites such as Google or LinkedIn and adding this data to your existing database.
This is a great strategy to get small amounts of accurate data, but it can be inefficient if your only goal is to get more bulk data.
There are many great places to get manual data from, but here are some general pointers:
- A company website: Contact details and plenty of other contextual information can be gained from specific company websites
- LinkedIn Sales Navigator: Great for B2B, but only if your lead has an active profile on LinkedIn.
- Google Maps: A more unlikely source, but great for small businesses.
- Yellow Pages and industry directories: A more traditional method of information gathering, but useful when targeting companies in a specific niche.
Data appending is a process in which new data elements are added to an existing database. For example, a simple case of this would be enhancing a company’s customer files with phone numbers, emails, or current addresses.
Appending your datasets means you can bring multiple data sources together — producing a more accurate and consistent data set than would otherwise exist based on a single data source.
An example of this might be extracting customer data from your CRM and marketing systems to get a better overall picture of each customer.
Appending data can also include techniques such as sourcing 3rd party data. This could allow you to merge postcodes and ZIP codes into your dataset.
Other examples would be weather data or traffic data — though data enriching location data is one of the more common techniques since this is readily available for most countries.
Data categorization sorts your data into categories, making it easy to analyze and retrieve. Essentially, it is the labeling and sorting of unstructured data to become structured before the analysis.
It falls into two distinct categories:
- Sentiment analysis: sentiment analysis is the extraction of feelings and emotions from the text. This attempts to answer whether the customer feedback was positive or neutral, and so on.
- Topication: determining the ‘topic’ of the text.
Both of these techniques should enable you to analyze unstructured text easily.
Data segmentation is a little more complex. Segmentation is a process that involves dividing a data object, such as a customer or product, into a group based on a variable of interest, such as age or profit margin.
You can then use this segmentation to describe the entity in greater detail and group similar entities together.
Common segmentation examples for customers include:
- Demographic segmentation: based on demographic data such as gender, age, occupation, etc.
- Geographic segmentation: based on country, state, or city of residence.
- Technographic segmentation: based on preferred technologies. This includes software differences such as Apple vs. Android, etc.
- Psychographic segmentation: based on personal attitudes, values, interests, or personality traits. This one is much more subjective and a little harder to segment.
- Behavioral segmentation: based on actions or inactions, spending/consumption habits, feature use, session frequency, etc. Most of this information can be collected from how customers use your website.
5 data enrichment tools and techniques for sales and marketing
Let’s look at some tools that can improve data enrichment to enhance sales and marketing.
Longer lead forms
Longer lead forms can be a trade-off between improved data quality and fewer leads filling out your forms. Yes, a shorter form will convince more potential leads to fill it out, but a more extended form will provide you with greatly enriched data.
In some cases, fewer leads filling out your forms may be a good thing. In an ideal scenario, you receive more information from high-quality leads, simultaneously spending less time on low-quality leads.
Try asking your leads for information beyond the basic email address and first name. Include the job title, company size, revenue, and location, amongst other metrics you collect.
Striking a balance between improved data collection and the length of the lead form can be tricky but definitely worth it in the long run. This is especially considering that this is one of the simplest ways to improve data enrichment without needing too much tech know-how.
Lead generation tools
Lead generation tools will help you collect important data about your leads. Many such solutions are available on the market. One of them is Leadfeeder.
Leadfeeder is a lead generation tool that identifies site visitors based on their IP address and domain and then pairs that info with their contact database. This lets you see a visitor’s company, company size, location, and the best point of contact.
In addition, the tool can provide behavioral data on your leads, such as which pages they viewed, how long they stayed on each page, what page they exited, and how many people from the company visited your site.
So using lead generation solutions, you can verify data about visitors, find new information about potential leads, and import it to your CRM or database.
For those unaware of Crunchbase, Crunchbase is a platform that allows businesses to gain information on private and public companies.
The content on Crunchbase ranges from information on investing and public information to funding information, founding members, and people in leadership positions.
Crunchbase has become so popular in recent years thanks to, in part, its verified and accurate data on businesses that match ideal target prospects as well as various other services.
The company also offers data enrichment services, helping you to enrich current lead data, build reports, and better understand your marketing effectiveness.
It’s especially worth considering for B2B companies that thrive off being able to collect business information from third-party providers rather than having to contact the businesses themselves.
Sending out customer surveys is a great way to understand your current customers and segment them. One of the problems with using data enrichment tools on the market is that everyone has access to them — including your rivals and competition.
In cases where everyone uses the same datasets, you can get ahead of your competition by generating a deeper understanding of your audience.
Gathering first-party data on your customers is a perfect way to make sure your data is accurate and relevant to only your organization. The best way to gather this data is by sending out customer surveys to ask your audience what they think and to gather information on them which can help segment them into distinct categories.
Once the audience has been segmented, you can target each slice with tailored upsells and better customer service.
This not only improves the perception of your company but works to generate revenue. Additionally, this helps with data enrichment by verifying the best contact points, their overall goals, etc.
These methods can be more time-consuming than some other methods on this list, but it’s hyper-personal to your audience and will be more relevant to your customers.
LinkedIn Sales Navigator is great for enriching cold calling data, making it a B2B sales rep’s best friend.
The platform provides deep insights into people and the companies they work for, allowing your sales reps to make cold calls more personal and to only pursue leads with the highest chance of converting into actual customers.
Sales teams can use this to find targets by searching for companies via certain filters (industry, location, etc.).
The service also connects to any CRM you’re using — meaning you can verify any data about prospective leads.
By matching up data from LinkedIn sourcing, you can ensure the right contact information for your prospects. As a result, your sales team can go into calls more confident and more informed about each lead.
Data enrichment equals better data
Improved data quality means better lead generation and, ultimately, increased profits for your business via more informed decision-making.
Ensuring your data is as good as possible is a key step in helping your business grow. As sales leaders with better data almost always end up on top.
Romana Hoekstra is a Content Marketing Lead at Leadfeeder, a B2B visitor identification software that tracks and identifies companies that visit your website. Currently, she is leading the remote-first content marketing team and crafts high-performing content marketing strategies with a focus on organic growth, SEO, high-quality content production & distribution. You can connect with Romana on Linkedin.Back to Blog