Unorganized leads data in CRMs can be a big issue for businesses for a number of reasons.

It can lead to lost opportunities: 

If businesses don't have accurate contact information, they may miss out on opportunities to reach out to potential customers.

It can waste time and resources:

Businesses may spend time and resources trying to contact leads who are no longer interested or who have moved on to other businesses.

It can damage relationships: 

If businesses send out inaccurate or irrelevant information to leads, it can damage relationships and make it more difficult to close deals in the future.

It can lead to compliance issues: 

Businesses may be held liable for fines or penalties if they don't comply with data privacy regulations.

This data is extremely valuable and now companies are under pressure to utilize more of their 1st party data given that 3rd party cookies are going away. Here are other initiatives that are impacted by this issue.

This includes ...

• 1st party data activation roadblocks and marketing reach limitations

• fragmented or incomplete views of customer journeys and key audiences.

• Incorrect view of pipeline and roadblocks to lead scoring capabilities

Each organization has its unique challenges for both people & tech aspects but what i have learned as top contributing roadblocks includes..

• Misalignment between marketing & Sales Operations

• The need to unravel contributing data sources 

• Overly customized CRM environments

• Bad routing of leads causing them to land in the wrong hands

• Prospect & customer data privacy handling limitations

Not simple stuff right, i know...but some steps can be taken by businesses to improve the accuracy and usefulness of their leads data and boost their bottom line. 

To avoid these problems, businesses need to take steps to organize their leads data. 

What You Will Need

 In-house SME on your business & data along with a credible external service that can help with the following items mentioned below.

1. People, Process & Alignment to Mitigate roadblocks to working synchronously between marketing, Sales & IT.

2.  CRM/Database Health Checks to evaluate the condition of your data

3. Technical Roadmapping for the following

• Standardizing data formats

• Implementing data validation rules

• Data governance plan

• Recurring data updates

An AI solution that takes the manual labor out of correcting, validating & attributing your leads.

There is no escaping the people and process part of the challenge which still may require internal or external workshops to get teams aligned and synchronized but this will take the latter half of the work and cut it down to a third of the labor and time.

How to Bring It To Life

Requirements gathering:

The first step is to understand the specific needs of the business and the users of the AI solution. This includes identifying the types of leads that need to be corrected, validated, and attributed, as well as the desired outcomes of the solution.

Data collection and preparation:

Once the requirements are understood, the next step is to collect and prepare the data that will be used to train the AI model. This data should be representative of the leads that will be processed by the solution, and it should be cleaned and preprocessed to ensure that it is in a format that the AI model can understand.

Model development

Once the data is prepared, the next step is to develop the AI model. This involves choosing the appropriate machine learning algorithm and training the model on the data.

Model deployment

Once the model is evaluated and found to be performing well, it can be deployed to production. This involves making the model available to users so that they can use it to correct, validate, and attribute leads.

Ears and eyes perked up yet? If so, see below on how you can take action.