Data is a valuable asset for any business. That’s why companies often invest significant resources in collecting and storing vast amounts of data. But, they don’t usually bother having strategies in place for proper data segmentation or usage. Additionally, much of this data ends up being forgotten and unregulated once it's stored away.
Also, companies often create data that is not relevant to their business operations. It's similar to Scrat from the Ice Age, who used to collect acorns – just to store them.
Here’s where data enrichment comes in. It’s a process that helps organizations enhance the quality and value of their data by adding or refining information. In this blog, we'll explore the importance of data enrichment and how it helps businesses make better use of their data assets.
Data enrichment refers to the process of augmenting an already-existing data profile. You can do this by sourcing and incorporating additional, relevant information to bolster value.
Data enrichment has a seemingly straightforward definition. However, executing it requires considerable effort and familiarity with the appropriate research tools.
On the surface, much of the data available is not particularly unique. Therefore, it contributes minimal value to your marketing efforts.
You must always aim to uncover truly transformative insights. For this, you need to delve into granular B2B databases. Further, you must devote time to carefully studying and filtering the available information.
Now, why do you need data enrichment? In other words, what are data enrichment benefits? Well, let’s start with some stats.
So, how are the above stats interlinked with data enrichment? For starters, there’s an undeniable correlation between data enrichment and lead generation.
You already understand that the effectiveness of any marketing campaign hinges on your prospect data quality. Now, subpar data can depress conversion rates for both marketing and sales. And this ultimately results in underwhelming revenue outcomes.
Next, your challenge lies in identifying the root cause of low-quality data. It can manifest in various forms such as:
So, this is where data enrichment and audit comes into play. By enabling your sales and marketing teams to enhance customers' data quality, data enrichment services can help for the following metrics:
So, you might be wondering, how exactly does this work?
Let’s move ahead to understand the processes involved in data enrichment to improve data quality:
Despite the proven benefits, only a minority of marketers utilize segmentation to tap into their customers' potential fully. And this is the case even when they’re armed with high-quality data.
By providing access to a wealth of information, data enrichment enables you to categorize customers based on criteria such effectively:
Plus, more refined segmentation translates to superior experiences for your B2B leads and customers alike. Why? It's due to personalized content that aligns with their specific needs and objectives.
Nurturing leads throughout the sales funnel journey is a critical aspect of a B2B marketer's role. Some leads require additional nurturing to convert into a sale.
By enriching data with pertinent information, you gain vital insights to nurture leads effectively across various channels. This is particularly true for social media – which has a large user base. After all, 59% of the global populace is active across social media platforms.
To make the most of your lead generation campaigns, your sales and marketing teams must set clear goals. It’s done by evaluating and ranking their leads AKA lead scoring. However, lead scoring done improperly can hurt your campaign's effectiveness.
Plus, this task becomes even harder when you have limited information to go on. Without reliable metrics, you're left guessing when scoring partial client profiles.
But there's good news. Data enrichment can help turn those partial profiles into complete ones. As such, it allows for more precise lead scoring.
Additionally, your sales and marketing teams can discover the most important information needed for lead scoring. By using these data enrichment tools together, you can reliably score leads and generate better results for your campaign.
Check out the below-given stats on personalized email open rates across different industries:
Enriched business data can help personalize your email outreach as you gain knowledge and insights about your prospects through it. As such, you can tailor your email messaging to their specific needs.
For example, let’s assume you're selling employee onboarding software to HR teams. Here, data enrichment can help you identify companies that are recruiting and likely facing onboarding challenges. You can use this information to make your email outreach more personalized and relevant to their specific pain points.
Managing one petabyte of data costs an organization around $650,000 annually. However, most of these data are unnecessary or drive minimal real value. Thus, by enriching your data, you can save significant costs. Here’s how:
This frees up funds that would have otherwise been spent on databases. As such, it allows for investment in other activities that positively impact your organization's bottom line.
A positive brand reputation hinges on having complete and accurate customer data. Incomplete or duplicate information can lead to missed opportunities and frustrated customers.
Now, this is particularly important for top-of-the-funnel demand generation strategy. Why? Here, the quality of data can make or break a campaign. Data enrichment helps:
Data enrichment can significantly improve your firm’s sales efficiency and boost ROI. This is because it provides clean, updated, and accurate contact lists. After all, investing significant funds in outdated contact lists can result in substantial losses. Data enrichment mitigates this risk by providing up-to-date contact information.
Plus, it offers other valuable insights that allow your business to know customers better. Armed with this information, you can identify opportunities for cross-selling and upselling. This further enhances your team’s sales performance.
Did you know? 58% of buyers don’t want to disclose their phone numbers. As per the same source, another 53% prefer not to release their addresses. So, what does this imply?
Asking for extensive information on a lead generation form can discourage potential customers from filling it out. To increase conversion rates, it is best to keep your forms simple and concise.
By utilizing data enrichment, you can keep forms short by only including the most essential questions about a particular client such as:
Once a lead is captured, you can enrich your customer profiles with additional details such as:
Business signals refer to time-sensitive events that indicate a good opportunity to reach out to a lead. You can identify these signals by monitoring a company's social media profiles and other media outlets. Examples of business signals include:
By using data enrichment, you can extract this type of information from the internet and add it to your contact database. This helps you prepare an effective pitch beforehand. Plus, it provides an opportunity to make your outreach more personalized.
Just because a lead wasn't interested or ready in the past doesn't mean they won't be in the future. Don't let an old list go to waste. Use data enrichment to add new information and insights about them. It could reveal new opportunities you never knew existed!
There are several data enrichment techniques used. Here’s a breakdown of the primary types:
Now, your next question may be: what’s the ideal data enrichment process for my organization? Well, the answer is simple. You need to be aware of the different steps in the process. So, here we go!
Identifying the target audience is crucial for any B2B marketer. And data enrichment can help you do just that. It’s true that B2B data enrichment vendors can provide a wealth of data points. However, it's important to use only the data that's relevant to your target audience.
Now, for this, you need to know about the major data types:
1. Socio-demographic Data
Enriching your datasets with socio-demographic data involves adding information about an individual's social and economic status, such:
It's crucial to know the purpose of your data enrichment project in advance. Only then, the enriched data will be relevant to your goals. For instance,
Adding socio-demographic data can help create personalized messaging and improve your targeted marketing efforts.
2. Geographic Data
Enriching your datasets with geographic data adds information such as:
This type of data can be helpful in various scenarios, such as:
3. Psychographic Data
Psychographic data refers to information about a person's:
You can use this data in your marketing and advertising efforts. Why? To better understand the target audience and create more effective campaigns. You can collect psychographic data through:
4. Firmographic Data
This means information about a company, such as its:
In the B2B scene, you can utilize this data to identify potential customers. Then, you can tailor sales and marketing strategies to their specific needs. You can gather such data points through:
5. Purchase Intent Data
Purchase Intent Data Enriching datasets with purchase intent data involves gathering real shopping data and product view frequencies. You can do this to gain a better understanding of a potential customer's willingness to buy. This type of data enables you to deliver highly targeted campaigns. Such campaigns aim to steer consumers closer to making a purchase decision.
6. App Usage Data
Enriching datasets with app usage data provides you with insights into the following:
By analyzing this data, you can:
Next, to determine which data to use, follow the following steps:
By using data enrichment in this way, you can:
As such, you can tailor your marketing efforts accordingly.
Next, it's important to identify the right tools and solutions that meet your specific needs. Think of it like creating a wedding guest list. You already have a clear idea of who you want to invite. And you don't want to waste time and money on unnecessary people.
So, to ensure you get the data you need, focus on quality rather than quantity. So how can you go about finding the right data? There are three main methods to consider:
Let's explore each of these options in more detail to help you make an informed decision.
1. Web Scraping
Web scraping is an extremely useful technique for importing information from the web into your file. You can use XPath queries in Google Sheets to retrieve specific data from search engine content or web pages.
For example, you can retrieve all the H2 titles of an article by writing an XPath query in a Google Sheets cell.
However, web scraping is not feasible on a large scale. Plus, it requires infrastructure beyond Google Sheets. So, if you're not able to write your own scripts, use an apt tool. It’s handy for web scraping and exporting structured data. Also, the data can be automatically synchronized with your tools using an API.
You can also use the following resources to collect data:
But keep in mind that the web is a messy place. Hence, you may need to clean up and transform the data before it's usable.
2. Manual Search
If you prefer a more hands-on approach, a manual search is another option to obtain information about your prospects. You can visit their company website, LinkedIn, or other relevant sources.
However, if you're dealing with a large number of prospects, outsourcing the research work to offshore platforms could be a more efficient solution.
3. Data Enrichment Service Providers
This is the simplest and easiest solution. These tools are designed to:
Revnew is a great platform to outsource your data enrichment requirements. Why?
You can also check out this case study on how Revnew helped the deep learning-powered Surface Scan™ generate awareness and 120+ quality appointments.
Understanding data sources involves more than just finding and sourcing your data. It's crucial to comprehend how your various sources correspond to each other across your tools. For example, capturing data about a certain company role, for instance, branding lead or content marketer, can be done in different ways:
Effective teams understand how these different sources interact with each other. Plus, they know how to prioritize them in data flow organization. This involves mapping:
For instance, the "Name" attribute may appear as "First Name Last Name" on Salesforce. But it shows as simply "Name" on Intercom. Hence, it's crucial to map data from all tools that store prospect or customer data. You should also consider all the data points that define your target audience.
The next step is to prioritize data sources by understanding their hierarchy. For example, you may find that data from lead forms is more accurate than 3rd-party data. Additionally, your data must be consistent. It should also be written in the same way for all sources.
As such, always select the most precise and complete writing format and apply it to all tools. You can utilize CDP (Customer Data Platform) tools to accomplish this. By the end of several iterations, you will clearly understand:
To distribute enriched data properly, synchronize all your company's tools. Only then, each tool will display the same view of each lead and customer. However, this is often not the case. Teams tend to start by enriching individual tools through plug-and-play integrations. And it leads to a siloed data organization.
A better approach is to choose a service that can enrich all databases across your company. It’ll enhance your core lead management system, such as:
This way, lead data can be synchronized between this system and other marketing channels such as:
Moreover, you must prioritize data sources. Plus, you should also understand how different data sources interact with each other. Thus, mapping data, flows, databases, and sources is a necessary step to achieve this.
The data should also be written in the same way for all possible sources to ensure homogeneity. Finally, your marketing team needs to enrich data to:
Marketing leads are usually managed by a separate Marketing Automation or CDP tool. However, it is essential to enrich leads for all marketing tools. Why? Marketing leads generally exceed those managed by sales.
To achieve the desired results, it is not always necessary to enrich all leads at once. This is particularly true when multiple layers of enrichment are involved. Controlling which leads to enrichment (Extraction) and the timing of the enrichment (Sequencing) is crucial.
1. Extraction
For extraction, B2B data enrichment services often charge based on a credit system. Therefore, it may be advantageous to remove leads that are of little value or those that you have already qualified for.
This strategy prevents unnecessary credit expenditure. Enriching your entire database is not advisable. Why? It’s pointless to determine if a contact is a content lead if the company has no interest in your services.
2. Sequence
Sequencing is equally crucial, especially when several layers of enrichment are involved. For instance, firstly, you can obtain data on people and companies. Then, distinguish good from bad leads. Secondly, you can qualify the technology environment of the good leads identified.
You can also choose to enrich the file with the IP address of your contacts. Next, use the company's domain name for the contacts whose IP you've retrieved. Finally, continue to enrich with firmographic data, email addresses, and so on.
In summary, sequencing enables you to avoid buying unwanted data from your supplier. It helps you progressively qualify leads – starting with the least expensive data points up to the most costly contact data.
Most B2B data enrichment tools excel at transforming cluttered and poorly formatted data into a clear, consistent dataset. However, the best marketing teams use data enrichment intelligently by focusing only on the data that:
It is crucial to identify the necessary data and data that isn't worth purchasing. After identifying the data, you need to make it usable. For this, you can use this 3-step process:
1. Conversion
B2B data enrichment services can provide you with access to previously unknown information about your leads, including the specific CRM they use. However, it's important to note that these services typically only identify a limited set of technologies through their API.
So, if you want to get a complete picture of your leads' tech stack, you may need to use additional tools and customize your emails, notifications, and other outreach efforts accordingly.
2. Categorization
Creating categories allows you to regulate the data flow. As such, the segments are enriched and synchronized with your CRM and other tools. Categorization uses enriched data to create and update:
3. Integration
The final step involves creating data flows between all your tools.
For example, requests for demos from leads that arrive via your form or live chat should automatically be enriched. Once leads meet specific criteria, they enter the "Qualified Leads'' segment. Then, they are automatically synchronized on the CRM and on Slack (to notify the sales team).
Automating the process of data enrichment is a fundamental aspect of the contemporary digital landscape. It is the backbone of various verticals, a few of which are outlined below:
1. Lending
Data enrichment is pivotal in credit scoring. Loan providers and banks access alternative and third-party databases to obtain a complete customer profile. It helps them to approve or reject potential customers based on the likelihood of default.
Data enrichment is indispensable for underwriting risk digitally. How? It equips loan providers with the information they need to protect themselves against fraudulent agents.
2.Fraud Prevention
Businesses can leverage data enrichment to reduce fraud rates by creating detailed user profiles. A single data point such as an:
For instance, there are email lookup tools that automate a search, which aggregates precise data about an email address, including:
This simple yet effective process can significantly decrease fraud rates in the long run.
3. Insurance
Insurance providers classify customers based on different data points and enrich their dataset to offer relevant insurance products based on risk levels.
Data enrichment can be used as a segmentation and targeting tool. As such, it enables insurance companies to refine their processes to increase efficiency.
Data enrichment can assist marketers in creating accurate buyer personas. Hence, it leads to effective targeting and higher conversions. Marketers can enrich customer data with:
As a result, marketers can:
Healthcare providers can enrich patient data to improve diagnosis accuracy and enhance patient outcomes. By analyzing patient data, medical businesses can:
If you want to improve your B2B lead generation through data enrichment, here are some best practices you can follow:
This means establishing criteria for what qualifies as "good" data. It also implies ensuring that all data you collect meet those norms. This can help you prevent issues like duplicates, inaccuracies, and incomplete information from affecting your lead-generation efforts.
Automating data enrichment is also critical. This can help you save time and resources by allowing you to collect and process data more quickly and efficiently. Automated processes can also help ensure consistency and accuracy in your data.
Using multiple sources for data enrichment is another important best practice. It enables you to gather a more comprehensive and diverse set of data. As such, it can lead to better insights and more effective lead-generation efforts. Consider using sources like:
Finally, it's crucial to keep data privacy in mind. Ensure you're collecting and using data in a way that is compliant with relevant regulations and industry standards. It can help protect your business from legal and reputational risks.
Data enrichment is not a one-time task. In fact, it needs to be performed continuously as customer data constantly changes. Failure to enrich data on an ongoing basis can result in irrelevant information and offers being provided to customers.
A well-executed data enrichment process is crucial for success in today's data-driven business environment. It ensures you get actionable, easily understandable, and valuable data. Hence, always choose the right data enrichment strategy and platform that meets your business objectives.