Today marketers can generate leads from a wide plethora of disparate sources, but this advantage has its share of challenges too. All sales leads are not accurate, complete and easily accessible. Sales and marketers are required to spend a fortune on invalid leads, time spent scrubbing and cleansing duplicates, standardizing good leads, and appending incomplete leads.
Which are 5 types of bad sales leads?
- Incomplete leads - not marketable and most of the times need additional data to make them actionable.
- Duplicate leads - Overlapping and varying information for the same prospect/customer
- Invalid leads - Fake/non-working email IDs, phone numbers, incorrect addresses, untargeted/ not interested customers
- Unstructured leads - Field formatting creates problems when routed to marketing tools or CRM
- Non-compliant leads - Captured ignoring regional or country’s laws/ regulations like GDPR & CAN-SPAM
What are the negative impacts of bad sales leads data?
The consequences of poor lead data not only affects the sales and marketing funnel; but runs deep and wide across the organization.
- Prevents sales and marketing teams from hitting revenue goals
- Bad sales lead data lowers conversion rates
- Hindering marketing and sales-development efficiency
- Reducing the reliability of measurement and analytics
- Decreases team moral and breeds mistrust amongst marketing and sales teams
- Unwarranted legal fines/fees due to non-adherence to data privacy regulations
- Increasing time spent on manual database updates after email campaigns
- Obstructing the prospect/customer experience
How to cleanse sales lead data?
Companies know that lead data quality and database integrity is similar to working out and eating healthy, but they are not equipped or prepared to cleanse sales lead data. The effects of bad quality lead show long after most of the damage is already done. Organizations should adhere to best practices to streamline every aspect of the process, right from manual data entry of leads, to scrubbing and standardizing lead files.
Data cleansing best practices:
- Defining and creating ideal customer profile (ICP)
- Identify and correct or reject dirty leads before they corrupt the integrity of sales data
- Start with cleansing top-funnel sales lead data
- Stop bad sales leads from website forms, third-party lead generating partners, events and sales representatives; entering your database
- Cleanse the sales leads to remove bounces and unsubscribes, update old customer information
Conclusion
Subsequent and regular sales leads cleanup is much easier. Regular data cleansing helps companies to surpass growth targets and scale up sales revenue contribution. Adhering to data cleansing best practices for managing manual aspects of data entry of leads collected from disparate data sources, and scrubbing and standardizing those lead files is mandatory. It empowers your organization to focus on strategies to increase conversions, create sales pipeline and impact overall revenue and profits.
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