| Question |
Answer |
| Best practices around assigning the actual numbers to the the attributes in the scoring model (what gets low points, high points, negative points) |
If it's your first scoring model, I would rank activities and/or demographic criteria in order of highest value to lowest value (not thinking about numbers, but just saying clicking a link in an email is a higher value activity than visiting a web page, etc) and then start with +1 as the lowest value item and increase by 1-3 as you move your way up. The best way to start with scoring is, to get started. Once your model has been live, you have real data you can then analyze and make changes to for your organization |
| What thoughts do you have around scoring differently for different audiences? When does it makes sense to have multiple scoring models within a single instance? |
It depends on how you're going to use the score. In most use cases, it doesn't hurt to allow more people to be eligible for your scoring programs. The one common caveat to that is if you are using the score to sync a person to sales, you'll want to exclude employees, competitors, etc from your scoring model. |
| can you make a separate trigger campaign to change the Total Person Score whenever Behaviour/Demographic changes? Just so you dont have to add the Person Score to each scoring campaign |
You can, but it's often more efficient (from a Marketo campaign processing step) to keep it within the campaigns that update the behavior or demographic score. |
| How can we put define different score basis on JOB Title for CEO or CTO and Developer? i.e. CEO/CTO should %2B10 and Developer %2B3 |
You can create different values - let's call it a high, medium and low value for Job Titles. You'd have three tokens (one to manage each value) and then in your smart campaign flow step, you'd add choices to say: if Job title = X, Y, Z -> change score to {{my.Job Title - High Value}}; if Job title = A, B, C -> change score to {{my.Job Title - Medium Value}}; etc. |
| what is the different between the default "Lead Score" field and the "mkto_Total Person Score" field, and why do you need both? |
You don't need both. The Lead Score (or Person Score) field comes as a standard field in your Marketo instance when provisioned. I have both in my Marketo instance because I append all field names with the source of the data, to help manage an instance that has lots of data sources - thus, I don't use the standard Lead Score field. You are welcome to use it though. If you chose to not use it and it becomes confusing to Marketo users, you can hide the field as long as it's not in use. |
| When the interesting moment is great than we use and what in type of campaigns? |
Interesting moments are typically created off of Marketo activity so it's recommended to score on the activity itself opposed to the interesting moment as it's more efficient. |
| Could you break out the behavior score into smaller sub scores if you wanted more granularity? i.e (Email behavior %2B website behavior |
Absolutely! You can use constraints or choice steps to get further granularity, depending on your need. |
| How can you score titles when there many be many differences in how the title is entered: |
You can use the contains function, or you can also create normalization campaigns that standardize your titles into functions as well. You may create normalization campaigns that say Job titles that contain "CEO, CIO, CTO, Chief" > update their job function field to be C-Suite. Then, in your scoring campaign you could say if Job Function = C-suite, increase their score X points. |
| can it be explained how lead scoring ties in to the use of Sales Insights? |
When you set up Sales Insight, you will need to choose 1 Score field that will populate the Stars and Flames within MSI. Thus, you'll need to build a scoring model and activate it to populate the Stars and Flames in MSI. You can customize how the stars and flames are set based on your score though (instructions on how to do that are here). |
| Our instance ignores using scoring tokens, and instead updates the actual score value in every Flow based on each Demo and Behavioral criteria. Why are tokens better than this method? |
I prefer using tokens because it makes it easier to make changes to the score values (all in one place, instead of having to check every smart campaign) and also allows for scale when cloning, if you have multiple scoring models. Overall, both approaches will get you the same result. Using tokens is easier and faster at scale. |
| additionally, is it possible to approach total score like a weighted factor analysis (wfa) model? i.e. you want to give behavior score 60% weight in the total score, and demographic only 40%? can you do some sort of formula action? |
Marketo doesn't technically have a "weighting" function, but you can create a work around to get the same result by managing the values. I.e. if you wanted a 60/40 weight, choose values that create that variance. |
| Is there any advanced functionality related to Lead scoring in Marketo Sky? |
Not that I'm aware of at this time, but you can review Sky features as they are released here! |
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