Skip to content

title: 🧠 In-Depth Training Plan for Client Call (GoHighLevel + Marketing Systems) date: {{date}} tags: []

🧠 In-Depth Training Plan for Client Call (GoHighLevel + Marketing Systems)

For project background, see the e9digital overview.

📅 3-Day Intensive Schedule

📆 Day 1: GoHighLevel CRM & Marketing Attribution

🎯 Objective:

Understand GoHighLevel's CRM functionalities and grasp marketing attribution models.

📚 Modules

GoHighLevel CRM Overview

Marketing Attribution Models

  • 📖 Marketing Attribution Guide – NoGood
    • Marketing attribution is what helps marketers and bussiness understand how and what contributed to a given sale and their sales in general. This allows them to fine tune their marketing stratigies
    • It also helps them see how their marketing efforts contribute to the main goals of the company
    • some of the key roles are:
      • Aligning sales and marketing: 59% of businesses believe that aligning sales and marketing is the primary goal of marketing attribution. This is because attribution helps determine the influence of multiple marketing and sales activities across the customer journey and defines credit at each touchpoint.
      • Optimizing marketing spend: This helps the company understand where they should point their marketing buget.
      • Enhancing Customer Experience: this helps them understand the marketing journey and when and where to place key touch points
      • Mearuring ROI
    • Types of Attribution Data:
      • Software based data relies on digital metrics and touch points to monitor user interaction this can be really granular and detailed but will also miss a lot of non digital indicators
      • Self Reported Data is the data that the consumer reports generaly in the form of surveys or questionairs. This data is very usfull as it can provide insitght into what the customer thinks effected him or her and also non digital indicators such as word-of-mouth and phisical advertisment. It is howver in general very inaccurate due to bias's and other factors.
      • Hybrid Data is a mix of the two previous catagories. leading to grater acuracy and scope however it can be very diffacult to implement this well.
    • Single Touch atribution models:
      • First Touch: is where the first interaction a customer has with your marketing (such as visiting your website or clicking on a facebook post) is given 100% of the credit for the conversion. This is great for identifying which channesl lead to the most brand awarness however they to not take any of the middle or final steps into acount which can be detrimental if the first step is not the crucial one in the customer journey
      • Last Touch: Considers only the last interaction of the user befor the conversion which is good for understanding how to push users over the edge on converting however if it is soley used it can lead to short sighted ness and missing brandawarness opportunities as it does not account for any of the leadup steps...
    • Multi Touch attribution models:
      • Linear Touch: Gives equal credit to all the steps in a customer journey for the conversion. This is good for getting a clear view of how the costomer interacted but can be faulty if it has incomplete information suchas the use of multiple devices and it does not take into account how things like seasonal channeles affect things.
      • Time Decay: This gives more weight to a touch point the closer it is in the journey to the conversion. It is prone to issues due to the fact that it does not consider the affect of the initial efforts and is generaly only good for B2B marketing.
      • U Shaped model: This gives 40% to the first and last touch point and then spreads the other 20% between the middle points. It is usfule if you want to see specific touchpoints while still haveing a overveiw of the situation. Most commonly it is used for e-commerce metrics such as ROAS and CLV...
      • W shaped model: is simaler to U shaped but it also focus on a middle point as well. It is generaly most usful in a B2B setting with well defined funnels that are easy to calculate. In most cases it is just to cumbersome and diffacult to set up as well as being to complicated to operate.
    • Data Driven Attribution:
      • Data driven models use machien learning and predictive analytics to decide which are the most valuble touchpoints, the algorithim determins which framework is best. This is very valuble for complex customer journeys witha a lot of touch points however due to the complexity and cost to opperate they are genealy only practical for companies with large bugets.
    • Custom Attribution:
      • Custom attribution allos a company to make up it's own rules about which touch points get credit. This is good for complex or abnormal marketing stratigies that other models have a hard time capturing but due the the complexity and cost of setting up and maintianing such a system it is only generaly practical companys with the budget and direct need for such a system.

Marketing attribution image

Attribution Model Use Case Pros Cons
First-Touch - Brand awareness
- Customer acquisition		 - Simple to implement
- Highlights initial touchpoints		 - Ignores the middle and end of the journey
- Overemphasizes first interaction
Last-Touch - Conversion Rate Optimization
- Customer acquisition		 - Highlights final touchpoints leading to conversion - Ignores earlier interactions
- Overemphasizes last interaction
Linear - Customer retention
- Customer engagement		 - Distributes credit evenly
- Reflects all touchpoints		 - Can dilute the impact of key interactions
- Doesn’t differentiate touchpoint importance
Time-decay - Channel optimization
- Customer retention		 - Gives more credit to recent touchpoints
- Reflects journey progression		 - Can undervalue initial interactions
- Doesn’t differentiate touchpoint importance
U-shaped - Customer acquisition
- Brand awareness		 - Emphasizes first and last touchpoints
- Highlights key stages		 - Ignores middle touchpoints
- Can be complex to set up
W-shaped - Customer acquisition
- Conversion Rate Optimization		 - Emphasizes first, middle, and last touchpoints
- Reflects multiple stages		 - Can overemphasize certain interactions
- More complex to implement
Data-driven - ROAS
- Channel Optimization		 - Uses actual data for accuracy
- Reflects true impact		 - Requires significant data
- Can be complex to implement
Custom - Specific business goal
- Complex journeys		 - Tailored to business needs
- Flexible		 - Requires significant data
- Requires significant data and expertise
- Complex to set up
  • Wrapping up
    • What to avoid in attribution modeling
      • Last click is not always "good enough' in general try to use multi touch instead.
      • Attribution models are NOT "one size fits all" you will use a different model for say a brand awarness campaingn then you would for a campaign that focus's on conversions
      • Models are not nessarily 100% acurate. It is important to constantly check them and make sure that the data is up to date and acurate.
      • Attribution models NEED regular reveiws and updates
      • Attribution modeling is not just for digital Channels. It is nessesary to intagrate offline data as well.
    • How to build Custom Data Attribution models:
      1. Decide and define clea, Detailed objectives
      2. Decide what constitutes as a conversion event
      3. Set a Lookback window. This means deciding how long between interactons the user goes before the last interaction no longer counts towards the conversion
      4. Give each touch point proper weight and prpare to review them on a regular bases
      5. It is nessasary to regulary test and evaluate your model including A/B Testing
      6. Utilize proper vendors and tools to implement properly. Google analitcs may be biased toward google channels undervaluing non google channels
      7. contenued testing and refinement

If you want to improve your marketing attribution, it is important that you first agree with everyone involved about the goals that you want to achieve in your organization. Understanding the questions that need to be answered will help you define the attribution models and methods you can choose from. Before you commit to a particular approach, evaluate your team’s capabilities. Although custom attribution gives you the best picture of your customers, it can be a complex process. Either opt for an out-of-the-box solution or choose to create your customized attribution model.

Attribution is not just about deriving data, but rather using scientifically validated approaches to understand the impact of different attribution models on business goals and KPIs. By selecting the right data and methods and maintaining a flexible, adaptable approach, you can gain a more accurate and actionable view of your marketing effectiveness, ultimately leading to better decision-making and higher ROI.

  • 📖 Attribution Models & Conversion Tracking – Two Trees PPC

    • A conversion does not nessesaraly have to be a sale it can be any goal that we are trying to drive the user towards such as a contact form submission or a newsletter sighnup...
    • Without attribution modeling it is almost imposible to utilize conversion based insights such as lead costs and per conversion cost
    • Essentialy you are comparing the paths of customers who did convert to the paths of those whoe didnt to understand the keypoints that are succeful and those that fail.
    • Thank you pages are the most common method of tracking conversions
    • Enhanced conversion can help track a multiple conversion prosses to the final sale "For example, enhanced conversions allow you to attribute multiple conversions and events to a final sale: perhaps the user signed up for your newsletter, added 3 items to their cart, and then visited the website from a remarketing ad to complete the final conversion (sale)."
    • Enhanced conversion analytic gives a better veiw of both online and offline data.

      While attribution modeling can sound like a minefield, it’s often something that goes unnoticed day-to-day. But, it’s a crucial factor to understand when optimizing campaigns and during data-driven decisionmaking. Without getting it right, you may end up making disastrous decisions for your brand.

  • 📖 Marketing Attribution: Everything You Need To Know – POWR Blog

    • This is the best one for scenario based examples, it pretty much covers the same topics that the other two do but it gives better exampels and explinations however it is less technical.

🕒 Estimated Time: 3 hours

I had ChatGPT test me exstinsivly in the subjects Disscused in day one

  • I need to study the procces for building a lead capture form
  • What is UTM data?
  • How do you use tracking links?
  • What is a drip email sequence and how do you build it? Day one test Note

📆 Day 2: Drip Campaigns & Affiliate Tracking

🎯 Objective:

Learn to set up effective drip campaigns and understand affiliate tracking mechanisms.

📚 Modules

Drip Email Campaigns

Affiliate Tracking

🕒 Estimated Time: 3 hours

📆 Day 3: Analytics Systems & Practical Application

🎯 Objective:

Master analytics tools and apply knowledge to practical campaign scenarios.

📚 Modules

Google Analytics 4 (GA4)

Data Analysis Fundamentals

Practical Tasks

  • ✅ Set up a mock campaign in GoHighLevel
  • ✅ Implement a basic drip campaign
  • ✅ Track affiliate links and analyze them in GA4

🕒 Estimated Time: 4 hours

🔧 Additional Resources

With this training, you'll be fully equipped to speak confidently and strategically about campaign setup, automation, attribution, CRM, and affiliate systems during your client call.