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Marketing lead scoring that works!

by Mo Faheem
Marketing lead scoring that works!

Dynamics 365 Marketing lead scoring is a simple model that uses the power of Azure to calculate based on specific criteria and variables a score for each active lead in marketing. The score is used to qualify the lead or direct it to the concerned sales team or department to nature the lead and close the potential business.

In another post, we explained how can we build and configure a lead scoring model. For more information on marketing lead scoring, read Microsoft detailed documentations.

This post is not technical, however, it aims to provide guidance on how can we create models that are not general and more business-specific.

Study the wining deals

The first suggestion I would give my clients is to build a good model based on the regular client portfolio on the winning history. Finding the buying pattern is the key to successful lead scoring.

Marketing lead scoring that works!
Lead scoring condition and score

Building a client portfolio

Building a client portfolio is a very unique experience for every business. The sales and marketing teams generally know their clients and when will they buy. This understanding happens spontaneously in the sales teams minds. The idea is to convert this understanding into conditions that if met a score will be given to the lead.

The condition depends on the demographic and behaviour of the lead, meaning the data has to exist on Dynamics 365 to be able to score it.

Sample of the questions are

  • Did the potential client recentley won a new deal that depends on one of the company’s products or service?
  • Do the potential client have a relation with one of the compatitors?
  • Does the decision to buy again depend on a previous relation or buying history?

The more question that we can answer the better forecast the model will provide.

Sync Tables with Dynamics 365 Marketing

To explain more, if a company maintains records of the new project awarded and the winning companies within Dynamics 365 Sales, we have to sync these datasets with Dynamics 365 Marketing to be able to score the leads according to this data. read more about syncing tables with Dynamics 365 Marketing.

The dataset has to have a direct or indirect relation with the lead table to be able to score the lead according to this data. read more bout the hops and the relation to the lead entity.

General rules and behavioral scoring

There are common rules that most businesses would use, such as the number of websites visits and the pages visited. Generally, this data show interest in the organization products or services and is a good indicator of buying singles. But again understanding the busing behaviour is different from sector to sector. For example, a real estate buyer has different behaviour if we compare it when the same person buys a car.

Build more lead scoring models

The thing that I witnessed many clients do is that they will delete the lead scoring model after a short period if they think it is not performing as they expected or overwrite it to try to fix it.

What I advised them to do is to keep the old model or to keep the changes as minimum as possible and create more lead scoring models instead!

After some time compare the model results together to be able to enhance the model and the score.

I believe that every business is unique as I mentioned earlier, and there is no secret formula to apply that would work for all businesses, even on marking interactions.

Learning curve

Therefore, the advice that I always say to clients is that Dynamics 365 Marketing is an experience and cant be compared with the other CRM models. Continous correction is the best method to build a working lead scoring the provides accurate outcomes.

This leads us to the following paragraph, how to measure the lead scoring.

Mesuring Lead scoring results and outcomes

Quantifying lead scoring is how we can decide that we managed to reach the best formula of the lead scoring. This measure can be done by answering questions, such as the following.

  • How many leads generated using this model?
  • How many leads converted in to sales that was orginated to the qualified lead?
  • The value of sales out of each model?
  • Number/value of new deals of new clients vs existing?

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