Most businesses today, like yours, have a Customer Relationship Management (CRM) platform to collect and use all the customer-related data relevant to make sales. However, when not properly organized and maintained, such bulk data can end up being a bane instead of a boon. This is where a solid Data Operations or data ops team process — including Data Hygiene, Data Enrichment or data deduplication — can supercharge the functionality of your CRM operations. Imagine having the behind-the-scenes magician that makes your customer relationship management system (CRM) work its charm.

Having a solid foundation on Data Operations via your CRM can make the difference between winging it and winning it. Particularly in the competitive B2B space, you always need to be ahead of the curve when it comes to building customer connections. CRM Data Operations can help you by crafting personalized experiences, anticipating your clients' needs, and staying one step ahead of competitors.

Why is Data Operations necessary?

Over 86% of CRM users rely on CRM data to generate sales forecasts. What could go wrong if the data in your CRM is incorrect?

Ryan, the Head of Sales at a reputed firm, made the mistake of creating his annual sales forecast from outdated CRM data. He ended up over-forecasting by millions of dollars, which unnecessarily inflated the budgets for multiple departments. In the end, despite spending a bomb, Ryan’s company miserably failed to hit the revenue target. All because some of Ryan’s team members weren’t careful enough to report sales data correctly on the CRM.

This is exactly where CRM Data Operations become necessary. If data goes wrong, everything else built on top will tumble. Go-To-Market team members at any organization, at all levels of seniority, use CRM data to go about their daily work, make decisions and even make sense of the outputs. From simple daily tasks like knowing whom to follow up with, creating campaign reports, sales forecasts to even revenue projections - Data Operations can be immensely useful.

Data Operations with respect to CRM

Data Operations play a pivotal role when it comes to Customer Relationship Management (CRM). CRM systems (think HubSpot, Salesforce) serve as the central hub for all customer-related information. Within a CRM Data Operations involve tasks such as importing data from various sources, updating customer records, segmenting contacts for marketing campaigns, and ensuring data is up-to-date and accurate

Types of Data Operations

Data Operations is usually not considered a glamorous job, but it is arguably the most important operational function in your GTM team. There are multiple processes that come under the ambit of Data Operations, for example:

Data Enrichment

Adding new and supplemental details to existing datasets to help your GTM teams make better decisions from your business data — that is precisely what Data Enrichment is. For example, adding missing contact details or firmographic/behavioral data on customers can enhance the quality of your data. Say you have a new lead that signed up on your website, but they have only mentioned their company name. Your Data Enrichment process would then involve fetching the company’s firmographic details from a Data Source, and adding it to the CRM.

So now, you not only know the lead and their details, but also the size of the company, the company’s revenue, primary industry etc. And this additional ‘enriched’ information can help you personalize your emails and discussions with your new lead. It can also help you decide whether the prospective lead is from an industry that you really sell to, other common attributes with your most successful customers and use this information to better qualify inbound leads.

Forbes survey shows that over 66% of customers want brands to address their unique needs and expectations when selling a product/service. CRM Data Enrichment can be the key to creating such a personalized buying experience for every customer. In fact, a lot of leading brands these days are adopting Data Enrichment as a core part of designing their sales strategy.

But how do you create a good Data Enrichment process?

Well, the only thing you need apart from your CRM is a Data Source. There are many tools in the market – Apollo, ZoomInfo, Lusha, Clearbit and one of the most prominent, LinkedIn. How you use these systems in your day-to-day depends on your company’s marketing/sales tech stack and how your sales processes work.

The biggest challenge seen with Data Enrichment processes is that it can start breaking apart as your data volume increases. Over time, records in your CRM get overwritten, duplicate data sets get created and you end up with a messy data set. This is where the other CRM Data Operations processes come into the picture.

Data Cleansing

Just as the name suggests, Data Cleansing defines the process of removing inaccurate, irrelevant or outdated data from your business’s CRM systems. Often dubbed as ‘data scrubbing’, cleansing is done to correct errors or inconsistencies in your existing dataset. Following this up with removal of duplicate records ensures your data conforms to a consistent format.

Think about all the old email addresses, repeated contacts or misspelled names that are still living in your CRM. Or may be a contact associated with two company records with just a difference of ‘Inc.’ in their names. Even a set of email IDs that hard bounced. When your sales team is set out on a mission to collate the relevant dataset for an important campaign, they have to wade through years of stale data. Having a solid CRM Data Cleansing strategy in place can help you save hours in such fruitless pursuits.

Difference between Data Cleansing and Data Enrichment

In CRM optimization, both Data Enrichment and Data Cleansing share one common goal. That is to collect the highest quality customer data, not necessarily a large volume. But it is a common mistake to confuse Data Cleansing with Data Enrichment. Though their functionality is often intertwined, there is a fundamental difference.

Data Cleansing focuses on rectifying errors and inconsistency while reducing Data Duplication. Data Enrichment involves enhancing the cleansed data with valuable and more specific information. Data Cleansing, followed by Data Enrichment, are together necessary to maintain a healthy, resourceful database for any business.

Data Hygiene

Data Hygiene is the broadest term used in the context of Data Operations for CRM. In fact, it can be used to mean different things when used in different contexts. But the underlying meaning is to ensure the common outcome – a clean, pristine data set in your CRM.

Recent research from Gartner indicates that dirty data (or a lack of Data Hygiene) is costing companies up to $15 million per year in losses.

When talking about Data Hygiene, we consider it in two parts. One is creating rules and guarding rails to ensure that incorrect data cannot enter the system. For instance, you can add a validation that the Email field in the CRM can only have email address format data. Or, you can set an automation that email addresses that bounce are automatically flagged for cleaning. This can be a part of your CRM Data Hygiene strategy.

The other part of Data Hygiene includes regular processes that help you and your team members tackle the ‘dirty’ data. Some teams even consider Data Enrichment as a part of the Data Hygiene process — flagging missing data fields so that those can be updated.

This dirty data can include inaccurate contact details, duplicate info, missing or delayed inputs. Data involving contact numbers, email IDs, addresses, job titles or last names are naturally prone to change over time. These can make your system less reliable and an expense burden without much ROI.

Regular data audits, setting a standardized hygiene check procedure and updating data in real-time can be good Data Hygiene practices to start with.

• Your first order of priority in Data Hygiene should be to set a data formatting standard across the company. This ideally includes capitalization, abbreviations, name prefixes, numbering formats etc.

• Regular review and evaluation of CRM data should be turned into a routine process for your sales team. Further, you can remove the data input fields that users are leaving blank more often than not.

• Between 30% to 70% of people reportedly change their contact details every year. Hence, such data must be updated in your CRM in real-time. After all, you don’t want your sales messages/emails being sent to the wrong contacts, or worse, not getting delivered to the intended audience at all.

• Most large companies with multiple departments have got their CRM data siloed. Ideally, data from one department shouldn’t be inaccessible to another. Especially for cross-functional departments like sales and marketing. The importance of data transparency and elimination of silos cannot be stressed enough when it comes to ease of doing business. This also comes under the ambit of Data Hygiene procedure.

Data Duplication

Quite a common problem in databases, Data Duplication or data redundancy occurs when a particular data gets stored in two or more places at the same time. This can happen in CRMs due to duplicate entry of the same data by mistake, and not always owing to human error.

CRMs like HubSpot consider one particular data attribute (like email ID) as the key identifier for a contact. But this wrongly assumes that every contact has only one unique email ID. Thus, people with multiple email IDs often end up being added more than once in the same dataset. Such duplication errors end up creating problems with your marketing campaigns.

Deduplication of CRM data is needed to avoid and eliminate such duplicated data added by default. The process identifies and merges duplicate records to maintain a single, accurate source of information. This not only reduces redundancy but also improves data accuracy.

Data deduplication can be executed by scanning your dataset for duplicity, followed by a resolution strategy to delete the same. Once deduplication is completed, it’s essential to clean up the dataset and repeat the operation regularly.

Tools for a Comprehensive CRM Data Operations Stack

To perform one or more of the Data Operations processes, you do need a comprehensive set of Data Operations tools. These tools work in harmony to ensure data is maintained, validated, and utilized effectively. Some of the essential components of such a Data Operations stack include:

CRM

A CRM system is the ultimate centralized repository of all data on leads, prospects and existing customers. Systems like HubSpot or Salesforce allow you to store, organize, and manage data while providing features for segmentation, communication, and reporting.

Data Sources

To acquire external data for sales and marketing campaigns, data sources can be an invaluable resource. Platforms like ZoomInfo, Apollo.io, RocketReach etc. offer access to an extensive database for contact details or company information on prospects you are planning to reach out to. Your sales team can manually collect such info and integrate the same into your CRM to use as and when needed.

Automations and Integrations

In Data Operations, automations and integrations enable the seamless flow of data between different systems and trigger actions based on data changes. In fact, DataOps automation technology is revolutionizing data pipelines.

Integration tools like Zapier or custom-built solutions can be employed to make Data Operations more efficient. A specialized CRM HubSpot Slack integration like Sidekick can also come in handy to manage day-to-day data-oriented tasks more productively.

Conclusion

In the near future, Data Operations are likely to evolve more in alignment with technology, fostering a far more effective data management process. Automation, machine learning and even Artificial Intelligence are likely to be incorporated into DataOps to orchestrate data infrastructure better.

On the other hand, many businesses are still in the dark about the importance of Data Operations. They are continuing to suffer losses and yield unsatisfactory results despite spending tons on collecting and preserving customer data in CRM. Actively incorporating Data Operations in their sales process can bridge the gaps in their revenue generation. Prioritizing Data Operations ensures that the data you rely on is not just an asset, but a strategic advantage.