#Marketing Cloud Engagement27 personnes en discutent

Hi @Mradul Srivastava

Not sure if helpful as our issue was with Microsoft, but we had a similar situation earlier this year. Everything our end was the same as it's always been but suddenly we had a lot of hard bounces to Microsoft email addresses only.  

The cause was an IP restriction on their end due to another sender in our shared IP pool. I was able to get this restriction removed with the help of Salesforce and Microsoft support teams.

Hi @Ionuț Buzatu,

This is probably not a broken Data Kit. A Data Kit carries the design (streams, mappings, Identity Resolution, Data Graphs), but not the connections or the source data.

Why it fails:

• Marketing Cloud streams: the connector is linked to a specific Marketing Cloud account and business unit, and credentials do not deploy. If Test is not connected to a matching account, the streams cannot be created. Identity Resolution and Data Graphs then fail because they depend on those streams.
• CRM streams with missing fields: a stream can only include fields that already exist in the target org. If the custom objects and fields (and field-level security) were not deployed to Test first, they are left out.

What to try:

1. Deploy the CRM metadata (objects, fields, FLS) to Test first.
2. Set up and authorize both connectors in Test manually.
3. Deploy in order: CRM streams, then Marketing Cloud streams, then Identity Resolution, then Data Graphs.
4. Check Setup → Deployment Status for the real error behind the generic message.
5. If it still fails, open a Support case with the Data Kit name, the failing component and the deployment Id.

 Hope this helps. If it solves the problem, please mark it as the best answer. And if you find the real cause, please share it, so other people with the same issue can use it. 

Good question, and one I'd like to answer properly, but the honest answer is that the shape of what you build changes completely depending on a few things you haven't told us yet. So let me ask rather than guess. 

First, a snag in the input list. You've got conversion rate, AOV and revenue generated as separate inputs. Those can't all be independent, either revenue is derived (contacts × CR × AOV) or it's measured from actual order data. If both, the calculator can disagree with itself on day one. Which is it meant to be? 

Is this a forecast or a scorecard? A pre-launch business case with sliders and ranges, and a post-launch "what did this actually earn us" report, are two different artefacts. Same formulas, completely different data sources and completely different build. Most of these tools get abandoned because they try to be both. 

Are your journeys always-on or campaign-shaped? For an always-on journey, ROI isn't a number, it's a curve. Contacts keep entering, conversion rate drifts, build cost is sunk and shrinking per contact over time. You'd need entry cohorts and a payback view, not a single figure. 

Do you already have holdouts running? This is the big one. Without a control group you're not measuring incremental anything, and no amount of formula design fixes that. If you do have them: are they persisted per contact, or re-rolled with Random Split on each entry? And is there a global holdout as well as per-journey ones? (Per-journey lifts don't sum to portfolio lift, and the gap matters.)

Where do revenue and cost data actually live? MCE has neither revenue nor margin nor cost of goods. That pushes the actuals half of this toward Data 360 / your warehouse / Tableau, with MCE contributing engagement and holdout membership. Is that available to you, or are you constrained to build inside MCE? 

Who owns the cost-avoidance assumptions? Cost avoidance is where business cases go to get manufactured. If Finance hasn't signed off on "cost per deflected call," it's a soft number and should be flagged as one. 

One last thing, said kindly: most of this question isn't really MCE-specific. Incrementality design, control-group methodology, margin vs revenue, cost-avoidance taxonomy: that's marketing measurement, and it would be true if you were running Braze or a spreadsheet. The genuinely MCE-shaped slice is narrow: how to persist a holdout flag so it survives re-entry, how to get engagement data out into something that can join it to orders, and whether a Cloud Page + assumptions DE is a sane place to put the front end. Happy to go deep on that slice here, since that's what this group is good at. 

For the measurement-design half you'll get better answers where the analytics and architecture folks hang out. The Marketing Architects group, or a Data 360 / Tableau group. Genuinely worth cross-posting; it's a good question, just a two-venue one. 

Tell me which of these apply and I'll happily go into the formulas with you.

Good question, Guru. The reason columns are missing: your script retrieves the DataExtension object, which only carries Name and CustomerKey. The COLUMNS live on a separate object, DataExtensionField, so you fetch them per DE. 

Easiest is SSJS Core (faster than WSProxy). For each customerKey you already have: 

var de = DataExtension.Init(customerKey); 

var fields = de.Fields.Retrieve(); 

var columns = []; 

for (var i = 0; i < fields.length; i++) { 

  columns.push(fields[i].Name); 

} 

Each field also carries FieldType, IsPrimaryKey, MaxLength, Ordinal, DefaultValue and StorageType, so you can capture data types and the primary key too if you want. 

So loop your existing DE list, call Fields.Retrieve per customerKey, and add that columns array into your JSON next to the Name and CustomerKey you already have. 

if this helps, please mark it as the Best Answer so it helps the next person, thanks 🙂

Your Salesforce AE should be on top of which SKUs are to be included here, as this can change quite frequently. The bottom line is, the MCE+ SKU is free of charge, but only includes very basic consumption. Once you start ingesting data to Data 360, running identity resolutions and unifications, as well as segmentations, the cost can quickly go up. So it is important to move slowly, and keep an eye on your Digital Wallet in Data 360, which gives you an insight about how many credits you are spending. 

It is always a good idea to purchase these flex credits beforehand, as you will otherwise be paying a premium price due to overage.