Bad Sales Leads and How to Cleanse Them

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Bad Sales Leads and How to Cleanse Them
Invalid, incomplete, duplicate, untargeted, unstandardized, and non-compliant leads fail to create a scalable and effective sales pipeline. Cleansing and standardizing lead data improves marketing-driven revenue and gives a full-funnel view of performance.

Sales leads are the lifeblood of any marketing campaign. To ensure that this data generates the defined campaign objectives, it is imperative that it be accurate, complete and easily accessible. Sales and marketing departments lose approximately 550 hours and as much as $32,000 per sales rep from using bad data. So it is critical that leads be thoroughly scrubbed, cleansed and standardized before being fed into any marketing campaign.

Adverse impact of bad sales leads



Missed targets due to low conversions



Impeded customer satisfaction



Lowered employee morale



High liabilities due to data privacy violations



Reduced reliability of performance metrics

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Which are the types of bad leads?

Bad sales lead data shows up as incorrect or incomplete customer contact details including email IDs, mobile and office contact numbers, duplicate customer profiles, unstructured customer leads, and non-compliant leads. Here are five major types of bad leads:

1. Incomplete leads

Incomplete leads

Incomplete leads require additional data to make them actionable. Missing contact and other information makes it difficult to qualify a lead.

Incomplete leads decrease program ROI, and if not fixed go “cold” or “bad”.

  • Though 18% of marketing budgets are spent on event marketing, leads generated from them are often incomplete.
  • Greater the number of fields on websites and landing forms to capture inbound leads, more is the volume of incomplete data.

2. Duplicate leads

Duplicate leads

Duplicate leads have overlapping information for the same consumer; due to multiplicity of sources and no single point of entry for records.

No mechanism to de-dupe, replace, correct, delete, organize and validate the data accentuates the problem.

  • Duplicate leads result in mixed messaging, over-engagement and decreased conversions. With nearly 7 decision-makers involved in the B2B buying process, and 50-90% of the purchase journey being done before a buyer interacts with a sales rep repetitive engagement attempts are detrimental.
  • Duplicate lead records also skew program performance measurements. If one from the duplicate records converts, it will pull down the average. And, if both convert it presents false growth pipeline.

3. Invalid data

Invalid data

Invalid leads result in improper utilization of budget, database and marketing resources adding to costs and hitting revenue goals.

  • 38% leads are Invalid
  • 30% of invalid leads are due to phone number
  • 28% of invalid leads are due to email IDs
  • 27% of invalid leads are because of a fake name

While you are reading this, in the next hour 59 business addresses will change, 11 companies will change their name, and 41 new businesses will open.

4. Unstructured leads

Unstructured leads

Unstructured or unstandardized leads come from sources like media partners, event organizers, webinars, lead vendors, and list buys. While they may be fine in terms of target audience or valid contact information, they pose standardization and integration issues when routed to CRM.

  • Leads don’t get integrated seamlessly, undermining business data integrity
  • Invalid, incomplete and duplicate customer data gets pumped into the database
  • Resources are wasted to standardize and integrate leads with existing database

5. Non-compliant leads

Non-compliant leads

Lead sources from inbound or offline tactics and third-party lead capturing mechanisms deliver sales leads that are complete and valid. But, such leads often ignore regional regulations such as GDPR and CAN-SPAM. Surpassing government legislations that limit how you acquire, store, use and share personal data can result in crippling penalties.

  • Marketing teams should ensure that their own hosted forms and landing pages comply with GDPR and CAN-SPAM
  • Lead vendors that collect prospect data on 3rd-party sites also comply to regional laws and country specific regulations

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A structured lead data cleansing process

46% of marketers with well-planned lead management strategies successfully follow up on more than 75% of leads. With over two decades of experience helping customers increase conversions and scale up sales revenues, HabileData best understands your business and specific marketing needs. We work on a meticulously designed, end-to-end lead cleaning process right from manual data entry of leads, to scrubbing and standardizing lead files.

HabileData delivers 17M+ cleansed & enriched records every year for a leading data aggregator company catering to the hospitality industry across the US. The structured and standardized data helps companies to design effective marketing strategies for higher lead conversion. Our data management teams push millions of records through a meticulous process including:

  • Validation against pool to filter out low confidence data for further processing
  • Authentication against valid online sources
  • Segmentation and assigning industry codes
  • Audit involving de-duplication, re-validation etc. through macros and scripts
  • Design of customized automation processes based on data structure and business requirements
Read the entire case study

5 step process to clean bad sales data

1. Define your sales and marketing leads database

Define your sales and marketing leads database

Ideal Customer Profile (ICP) is the first step towards a clean and accurate database. Clarity about what type of data should exist in the database drives your marketing efforts to generate quality sales leads.

  • Well-defined ICPs drive compelling business results, including faster sales cycles, higher conversion rates, and greater average Annual Contract Values (ACV) and Lifetime Values (LTV).
  • Sales and marketing teams can work on high-value accounts with a focus on scalable and repeatable strategies to engage and convert tier one accounts.

2. Locate the causes of dirty data

Locate the causes of dirty data

Database quality and marketability depends on your ability to identify, correct or reject dirty leads, before they corrupt its integrity. Ensuring regular update and eliminating bad leads is equally important.

  • Multiplicity and diversity of sources and strategies generating leads creates variations in lead quality and makes it difficult to tell the good rom the bad.
  • Rising frequency of people switching jobs leads to shorter shelf life of these contacts.

3. Prioritize your data quality problems

Prioritize your data quality problems

Start and focus on cleanup of existing top-funnel lead data before implementing the preventative efforts. To save your existing data from getting polluted and cleanup efforts getting wasted:

  • Figure out the type(s) of bad lead data presenting the biggest issue for your team.
  • Are there leads outside your targeted account type/personas?
  • Does lead data comprise of invalid contact data?
  • Are majority issues specific to certain channels?

4. Stop bad data from entering your database

Stop bad data from entering your database

Map your data quality issues with lead sources including website forms, third-party lead generating partners, events and sales representatives. Create rules to restrict who imports the lead data and how.

  • Hire data cleansing experts to de-dupe or merge contacts and provide basic information about those contacts. Lead data they prepare should adhere to the customer persona you defined.
  • Outline and implement standard data cleansing process to ensure all acquired leads are ready to use or ready to be uploaded to your master lead database.

5. Get the bad data out

Get the bad data out

Now is the time to take care of bad data which has already entered and sitting in your database eating up overall productivity and efficiency. Regular data cleansing process:

  • Remove bounces and unsubscribes from your database to prevent contacting customers who are not interested. It will ensure ongoing compliance too.
  • Remove leads that do not fit your target audience criteria. Technological assistance in form of automated data cleansing is of immense assistance here.
  • Automate the process of invalidating out of date contacts, finding job changes, and updating phone numbers and titles from email signatures.


A strong and holistic approach to sales and marketing data cleansing helps you to maintain data hygiene and raises the win ratio of your marketing strategies. After a first mega data cleansing drive; subsequent and regular clean up acts are equally important. This mandates a robust, well documented leads cleansing process in place, managed by data cleansing experts.

Automating your data cleansing tasks right from data entry of leads to standardizing, scrubbing and validating them has proven to give rich dividends. And businesses the world over are fast recognizing the critical need for technology-backed data cleansing processes to boost their sales growth.

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About Author

Author Chirag Shivalker

heads the digital content for HabileData, a global data management solutions outsourcing company, rated as one of the top BPO companies in India. Chirag's focus has been on enterprise wide data digitization, data governance, data quality, and BI capabilities.

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