Introduction
In today’s study, I would like to focus on Lead Scoring and how someone could achieve it with minimum monetary investment. I will try to outline the solution I have implemented for a client from the e-commerce industry. The company, a producer of 3D optical systems, was facing a challenge in classifying its leads and determining which lead is the most likely to turn into profit.
The solution was developed over the course of 2 weeks, which included workshops, solution design, delivery, and UAT (user acceptance testing).
First step - investigation
The first step to any Salesforce solution is realizing that there is a problem. I always make sure to spend time with the end users. It was no different that time around. I noticed that the sales reps are contacting their leads mostly at random or on the date of creation. I also noticed that some male associates prioritized reaching out to female prospects. While working with stuff you are most comfortable with is good, this could have been optimized sales-wise.
After understanding where the problem was, I invited the Sales Manager and Marketing Manager for a 60-minute initial meeting. After outlining the problem and the initial estimation, I have gotten the budget approval. It is always good to give your client an assessment of costs, even if it is a little far-fetched. Your Product Owner will need that for any budget planning and the Project Manager for resource planning.
Second step - solutions
We were considering two solutions to that problem. The first one was Einstein Lead Scoring. The considered pros for Einstein Lead Scoring were:
- Machine learning and the possibilities it brings
- Einstein predicts which of your current leads to prioritize
- Pre-defined dashboard with reports that include:
- Average Lead Score by Lead Source
- Conversion Rate by Lead Score
- Lead Score Distribution: Converted and Lost Opportunities
Cons:
- Extra licensing costs
- Ten days refresh rate
- Maintenance required
The second option that was under consideration was manual lead scoring. We have defined key fields on the lead and assigned scores to them. We wanted the maximum score to be 100, but there were also minus points.
Key fields and their scores:
- Phone number = 50
- Title = 15
- Department = 15
- Company = 10
- Country = 10
And for the negative points:
- 60 days without conversion = - 30
- No phone number - 15
- No title = - 10
- No department = - 10
An example formula that you could use for adding the points would look somewhat like this:
The formula checks by looking at each field; if the field has no value (isblank), it gives zero points. If it has some value, it gives points based on the value provided after the “0”. It adds the score for the defined fields within the formula for a maximum of 90 points.
Pros for this solution were:
- Cheap and easy to achieve quickly
- Minimum maintenance required
- No extra license is needed
- Based on sales rep expertise, what information is key for closing out the deal
Cons were simply that it is not machine learning and lacks the possibilities of Einstein. However, the deciding factor was, as often is, budget and ease of maintenance. Hence, we have gone with the formula field calculations.
UAT
After the solution design and implementation phase came the most important part of the whole process - user acceptance testing. No matter how technically perfect your solution would be or how much time you spend polishing your initial design, if users do not find the solution helpful and useful, all your efforts have been in vain, and your client’s budget has been wasted. I do not have to tell you that respecting your client's budget is the quickest way to his heart.
We ran a two-day UAT session with both the Sales and Marketing teams. We’ve gathered user feedback and implemented the user's suggestions that management validated. The only thing left was production deployment and training; users were ready to work on our solution.
Conclusion
Thanks to gathering feedback from users to realize where the issues were, proper stakeholder engagement, and following a proper solution lifecycle, we’ve managed to deliver solutions on time and within budget.
The key objective was to minimize managers and sales team involvement, realizing how valuable their time is and, at the same time, keeping them in the loop so as not to miss too much with our assumptions.
The result? Happy team, happy client, money in the pocket.
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