Data quality is never an accident. However, most companies discover data issues randomly. According to the an Experian benchmark report, “Most organizations say data quality issues are detected when reported by employees, customers or prospects, and fewer than one in two companies conduct proactive data audits to discover data quality issues.”
Understanding Data Quality Management
It’s time to be more proactive and plan for data quality. Here are some hands-on strategies to improve data quality in your organization.
1. Establish a Data Capture Approach for Lead Generation
Ideally, use Marketo forms (embedded or native), or a server-side form post for lead generation. Leverage restricted values, field validation, or field pre-population to allow users to update their information on the form. By helping users fill in the form automatically, you dramatically increase the likelihood that they don’t abandon the form and actually submit it. Tools like RingLead Smart forms, can help auto-fill certain fields on the form itself, and enrich remaining fields with contact and company data on the back-end making it easy for the user to fill out, and easy for the sales rep to discover more information about the lead.
2. Be Aware of How the Sales Team Enters Data
Sales teams often create leads or update records with new information. Make sure that they complete the necessary fields to ensure accuracy and consistency. Incomplete data entry may be due to a lack of understanding of how it will be used. For example, the email address may not be as important to the Sales teams as the phone number, but it is critical to Marketing, since it’s used for communication, and serves as a key identifier in the Marketo Lead Database. Conduct training with Sales to increase awareness of the necessary data points, avoid text fields in your CRM, and instead, leverage pick lists. If you don’t want certain fields to be updated, set them to read-only. Enrichment tools, like RingLead DMS Enrichment, can help sales and marketing reps auto-fill over 100 different contact and firmographic data fields within minutes, giving each team the exact data they need without any extra work.
3. Stop CRM Sync Fails
CRM synchronization can often be overlooked by both Marketo and Salesforce administrators, however, the implications can be costly. If a net new lead fails to sync, the lead will remain in Marketo only, and will not show up in Sales views and queues. Failed sync for an existing lead will cause any new information to be lost including data field updates (such as additional profiling, product interest, etc.) or Requests for Information (RFIs). Sync failures can be a result of many issues, such as performance slowdown, bandwidth limitations, field-level visibility, non-matching validation rules, etc.
In Marketo, you can subscribe to receive automatic failed sync alerts (in your Notifications section), but I also recommend requesting top syncing fields report from your Support Engineer and setting up a smart campaign, and a static list with daily reports that uncover any leads with failed sync from the previous day. Troubleshooting those will help pinpoint and fix the issues quickly.
4. Prevent and Fix Duplicate Records
Duplicate records are typically identified by email address; however, in B2B instances, it’s not always enough to find all duplicates.
Duplicates cost you money, confuse sales, and break marketing automation process. It is best to catch duplicates immediately and sometimes deleting this duplicate record – before it has history and activity associated with it, could be the best solution. To do this, set up trigger alerts to receive notifications automatically. Run weekly reports with the records of existing duplicates and investigate sources and processes that generated duplicates. This way you can both prevent, and fix systemic issues. Duplicate protection tools, like RingLead DMS Duplicate Prevention, stops duplicates from entering your CRM in real-time from list imports, web submissions and manual entry, keeping your database clean and up-to-date at all times.
5. Normalize Your Data
Data normalization is important because data is collected from various sources and may include a variety of spelling options, e.g. spelling of the United States as U.S. vs. USA. This directly impacts smart lists, scoring, segmentation, etc. As humans, we may see United States, U.S., and USA as the same country, but marketing automation platforms and CRMs see them as three different data points. Therefore, data standardization is crucial to establishing that singular approach to entering a data point. You can set up normalization smart campaigns in Marketo or utilize a third party data normalization tool, such as RingLead Data Management Solutions (DMS).
In summary, you have to become the catalyst for this and drive awareness. Implementing data quality processes and strategy will help your organization be more efficient and realize higher revenue. Remember. data quality is not an accident – it takes time and requires a thoughtful approach.
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