Your organization's sales team deals with large stores of data around customers and prospects captured in your Customer Relationship Management (CRM) system. Say your customer changes their role in their organization, their contact details, or other aspects of their profile - their data in your CRM can become stale if not updated and enriched periodically.
Each of these contacts in your CRM represents a relationship initiated and nurtured carefully by your sales team. As soon as a record is added to your CRM, it starts decaying, i.e. the aging or obsolescence of data begins. If this data is not updated it can lead to a waste of resources and expenditures on storing unusable data or uncontactable warm leads.
It’s been reported that close to 4 million US workers changed their jobs every month in 2022. Attrition is just one of the many reasons that a majority of your prospect lists tend to contain outdated CRM data.
Read on to learn more about what causes your CRM data to go stale. Furthermore, we will delve into the various ways that you can employ to resolve challenges faced with decaying, stale, or outdated CRM data.
Signs your CRM Data is Stale
Every organization must ensure that its CRM data is clean, complete, and up-to-date, along with ensuring that the customer relationships and hierarchies are clearly defined. If you fail to satisfy any of these criteria, your CRM data stands a chance to go stale quickly. But how would you recognize when your CRM data is stale? Data cleansing and enrichment efforts must be employed immediately when any of the following signs start showing up:
1)Ineffective Prospecting:
The competency of the prospecting effort from the sales and marketing teams has a lot to do with the quality of data stored in your CRM. If your prospecting efforts, namely researching your prospects, sales pitches, and follow-ups with prospects are based on stale CRM data, you will find that these efforts tend to lead nowhere, wasting precious funds and time.
2)Irrelevant Outreaches:
If your marketing outreach strategies are based on old information, it can detrimentally impact the outcomes. CRM info such as phone numbers, addresses, financial details, and product portfolios of your prospects may have changed. Irrelevant or outdated data points lead to bad email hygiene, fiercely limiting your outreach efforts.
3)Low Response Rates:
Stale data-driven sales and marketing campaigns do not guarantee nearly the same response rates as those of healthy CRM data-based efforts. Such campaigns can end up spamming your audience, while the number of useful responses descends. All this while your data keeps decaying and without regular maintenance of data hygiene, your cost of acquisition will go through the roof.
4)Outreach to Old Contacts:
If data duplication occurs in your CRM and it is not kept in check, there may be scenarios where the same account appears to work for multiple organizations. As these accounts get contacted repeatedly the marketing expenses and reach will go to waste.
5)Spike in Demand Generation Budget:
Without actionable customer information, you would not be able to develop data-driven strategies to create targeted awareness and generate demand for your product. So utilizing stale CRM data to prepare a demand-generation budget is a futile activity, as sales teams are likely to keep increasing the budget due to the muted response.
6)Poor Connection with Contacts:
If your sales reps base their customer communications on bad data, there are plenty of possibilities for customer or account mix-ups, duplication of effort, undelivered or incomplete messaging, and lack of a feedback loop.
7)Not Meeting Sales Forecasts:
All the above factors ultimately lead to the sales forecast numbers never being met. Forecasting sales numbers is a pointless exercise if it is based on irrelevant prospect information.
Why Does CRM Data go Stale?
Organizations in the B2B space, dealing with recurring clients must ensure that data hygiene is maintained since there is a chance that large volumes of client data may become stale or get duplicated. Data decay occurs when the information in your CRM can no longer be used for assessing a prospect's viability. Activities that can lead to stale data entering the sales and marketing workflows are the following:
- The data becomes stale as soon as it is created. Relying on a source database with weekly or bi-weekly data updates can further aggravate data decay. If the records are not updated frequently, it drastically reduces the data's effectiveness.
- Manual collection of data to enter into the CRM can attract human errors into the system, in the form of missing or duplicated data points. This is further aggravated if the data is being collected from multiple disparate source databases.
- If the source database's data structure changes, i.e., new tables or columns are added, not all the data points are updated to fit the new structure.
How to Fix Stale CRM Data Problems?
There are a number of key stages in the process of resolving stale CRM data issues. When it's time to convert a prospect into a lead it's all about engaging with them effectively using the right data at the right time. Throughout your sales pipeline, it is pivotal to know the customer inside out which is not possible without accurate CRM data. So here are a few techniques to ensure that the CRM data does not go stale:
1)Data Cleansing:
This technique involves a process of enhancing the quality of data wherein erroneous data of any kind is removed from the CRM, either manually or with an automation tool. For different types of data errors, different methods of data cleansing are implemented as follows:
- Data Deduplication, which is the removal or merging of duplicated data points related to contact details, company information, and data around deals. Some data points with partial overlap are also candidates for deduplication.
- Structural errors related to naming conventions, incorrect capitalization, and typos are removed.
- Field Rules implementation is the next step, wherein the data is fixed so that it matches its field of entry in terms of format, data type, and convention.
- Missing data, null values, and fields with missing records are identified. Data is entered wherever it is missing, but it is to be done cautiously without damaging the integrity of the data. Another less ideal option is to delete fields with missing data but this approach is strongly discouraged since it may alter the structure of the data table.
2)Data Enrichment:
Repairing inaccurate information by incorporating internal and external data to build a more refined profile of existing or potential customers is known as data enrichment. This helps create a centralized and authoritative set of records by combining multiple data sources. This unified database helps the sales team to get a more in-depth understanding of the target audience.
The following are some techniques of data enrichment that are implemented when specific business use cases arise:
- Data Appending, is the amalgamation of data from disparate sources, including third-party sources, to create a more detailed and powerful representation of the customer profile.
- Firmographics Enrichment, which is the enrichment of company-related data which pertains to the employee size, purchasing approach, business structure, etc. comprehensively segmenting B2B prospects to build targeted sales channels around them.
- Industry Enrichment, meaning the integration of industrial context into data enrichment. Campaigns can be designed in a way that helps a customer identify companies within their own constituent industry, basing the sales campaign structure on this information.
- Parent-Child Relationship Management, wherein the prospects' designations and hierarchies in their organization are identified for a more drill-down design of sales campaigns around them. Equivalent hierarchies falling under a single account are segmented to further reduce the likelihood of stale CRM data.
How Daffodil Software Helped a Leading US-based Company to Fix its Data Problems
The client is a San Francisco-based billion-dollar proprietor of one of the world's premier customer engagement platforms. Daffodil Software helped with the client's problem of data decay that it was facing for over 1 million contacts, both old and newly acquired ones, in its CRM. Our data stewards went through over 5000 data records daily and the challenges were tackled with a three-pronged data enrichment approach - firmographics enrichment, content enrichment, and hierarchy management:
1)Daffodil enabled the client to get a more in-depth view of the organizational data with firmographics enrichment. Companies were classified and segmented based on criteria such as company size, market share, revenue, and more for deeper insights into the prospect lists.
2)Content enrichment improved the overall data accuracy and quality by cleaning, completing, and updating records using additional information from disparate applications and data sources. Valid and invalid data were analyzed and verified.
3)Hierarchy management was carried out by the Daffodil team so that the client could view, navigate, and analyze multiple parent-child relationships within the CRM data.
Ultimately, the client's database of over 1 million accounts was enriched with more than 95% accuracy. The client was enabled to leverage the enriched data records to provide custom recommendations to its prospects. Find out more about this case study, here.
ALSO READ: What is Bad CRM Data and Why Should We Enrich it?
Optimize Your Sales Strategies With Enriched CRM Data
Stale CRM data is detrimental to the entire sales pipeline, but with the right data enrichment partner, you can develop effective marketing and sales campaign. With a well-planned strategy to remediate the root causes of data decay, your sales campaigns can become more cost-effective and targeted.
