Indrajit S

After that, I joined Infosys. Then I got trained on the Salesforce admin platform development and AWS. After that, I created a project. In it, I got the chance to work as a Salesforce marketing cloud developer. And then I worked for more than 2.5 years. I worked on two different teams. One team developed email campaigns from scratch, creating email templates, journey builders, automation studios, and creating data extensions based on campaign requirements. On another team, I mostly worked on mobile post notifications, and sometimes I got the chance to make small changes to game templates, such as changing hero images or CTA links. When creating mobile push notifications, I worked on creating the push notification messages and added previews to Jira tickets for the plan. Once it got approved, I would then schedule the push notifications on the client's requirements. This is the overall work I did in my role.

Suggest a way to manage bonuses effectively using marketing cloud capabilities. There are many types of bonuses, which we can see, such as soft bonuses, hard bonuses, technical bonuses, and black bonuses. However, in some cases, we are not able to do anything with technical bonuses due to some technical issues or data issues. In those cases, we're unable to manage them. But in cases where the email ID is not found or the one is not valid, we can remove the subscriber key from the data to get the percentage of click-through rate. This will help us get a high click-through rate, and then we can effectively manage the Salesforce marketing cloud capabilities.

How could you release an AMS script to personalize content based on churn customer data in general? Apps Script is a programming language that will be used in Salesforce Marketing Cloud. Mostly, it's used for personalization and to segregate country conditions based on subscriber attributes. Like, we can personalize the content based on their preferences and based on their use cases. Like, if we're sending a mail, we can use the AMS script to send two different contents to the customer based on their general preferences, like mail and payment. We can use the AMS script to send different contents to the customer based on their gender preferences. And also, we can use an AMS script in the subject line to make sure to test with subject lines that are attractive to customers, so that we can get more click-through rates and open rates, resulting in high ROI in the campaigns. And also, we use AMS script to personalize content by adding first names in greetings, like "thank you, customer name" or "dear customer name," and opening email templates or messages. Then we can add the contents and messages needed. And also, we can add references based on customer purchase history. Or we can send recommendations based on the search history of the customer. So, an AMS script is much utilized for personalizing separate contents for each and every customer.

What. In automation, we can see there is an activity called file drop. In that file drop, we can extract files, like upload or import, files from and into marketing cloud. So, whenever we are syncing the CRM, like Salesforce CRM, we can indicate sales code or service code into the marketing cloud so that we can get the data from sales and service code. And then we can do some segmentation, filter the audiences, and send communication to the customers. So by using the automation file drop activity, we can drop files from various clouds, and use it. Another way is that we can directly sync those data from into the marketing cloud, like synchronize in data extensions, so that in the detection time, we have values that are get from Sales and Service Cloud, that are connected with the Salesforce CRM. And, how we can integrate, like, in emails today, we can go to that email studio and then configure. In that, we can see there is an integration click button. Once we click on that, we can integrate those cloud, CRM login and password. And after that, it will get integrated into the marketing

Complex segmentation strategy, I would say, is one that I got a chance to work on, sending air camera products to some customers so that I have to get the content from 2 or more days, including their abandoned cart details and the searches they made and their previous purchase details. So based on this 3-deck section, I have to filter out 2 or 3 products from the high-priority ones so that I can recommend them to the customers based upon their preferences. It would be a bit difficult to implement this segmentation in the marketing tool. And other than that, I used one automation, which I worked on, a view called EMEA. It consists of Middle East, Europe, and Asia. In there, I have so many countries, and the countries have different language preferences. So in order to send them a bit of email communication, I need to segment each and every country under their language preferences. For that, instead of creating one by one, I used the automation tool to segment all the customers based on the countries and language differences and store them in a new data extension. So it will save my time and also make it efficient to process.

Components of SIN classification. Explain what they are used for. SIN classification is used on sending email messages via marketing tools. Send translation contains 3 things: central profile, delivery profile, and the CAN-SPAM classifications. In that, the sender profile contains the sender's IP address and the configurations of headers and footers. In delivery profile, it contains the from name from which the email is sent and also the reply email. The CAN-SPAM application contains CAN-SPAM classification, which contains two types of emails: transactional and commercial emails. Transactional emails do not need to have an unsubscribe mechanism or any other profile center article. But in commercial emails, we need to add the unsubscribe mechanism, and they need to follow some of the rules that are provided by the CAN-SPAM governance so that it will not get flagged as spam and follow the GDPR act, so that the mail will not get into the spam folder or something like that.

And the common mistake we're taking is for producing Salesforce market and our strategy to avoid. The common mistake we can take is that the data extension names are sometimes the report name will get different. It is case sensitive, so we don't get the desired results. We use the attribute tabs in the SQL query or when we are creating SQL, so that we can drag the data action and directly use the attribute instead of writing manually. This will avoid a common mistake that we are making when we are writing a spell code. And other than that, when we are combining joins, when we use some join operations in both in two different data segments, we will make sure that the book of the days contains a common attribute so that we can get a custom, structurally key as a power of reference, like an inner join, outer join.

To set up a multilingual dynamic email campaign, a multilingual dynamic email campaign is inactive. It's nothing but multilingual is preferred in a single email template, where we can have different types of messages based on the language preference. For example, if we take India, we need to segregate different languages such as Marathi, Gujarati, Tamil, Telugu, and Malayalam. So, based on the customer location, they will get their preferred mail. To set up a multilingual dynamic email, we can add countries and language preferences under the content for a subscriber, which should contain their country and their language preference. The dynamic contents are stored on different data access, such as English content, Hindi content, Tamil content, and Malayalam content. When integrating this, if a customer is in India who prefers to get English content, we get the English content from the data extraction and display it on the email messages or mobile communications. Based on this, we use a transcript to get the multilingual mail dynamic content from separate databases and insert it into the email.

Proposed solution for AB testing. Lifelong's subjecting the same email for example, if we take a campaign like a birthday campaign, so we can use one subject line with the normal birthday message, "Happy birthday. You wish you a good year ahead." Then we can give a subject there. And in another subject, we use some personalization, like, "Happy birthday, the customer name." So that we can test the different types of emails based on some rules or percentage, like first 10 percent we'll send to the AB testing. And based on the send, based on the click-through rate and the open rate, we will set the winner. And the remaining emails will be set to the winning version of the same email in the marketing flow. So based on the winning ratio, we can schedule the emails.

What happens if we take the day by an email? The bill that is not written and not expected in marketing. First, I like to console each and every attribute that is placed from data accessions so that I can check whether the attributes are fetched perfectly from the data accessions. Like, if I use the first name, last name, and also email address and under their location, I want this from data extension. I mean, once I fetch the data extension from and I fetch the data from the data action, I use the HTML tags to get this attribute displayed on the email templates. If it is displayed, I will then work on some conditions or rules based on the attributes that I get from the data. For example, if a customer has some membership like golden membership, silver membership, or some premium membership, based on the subscription, I will render the UA. For that case, I will first check for the status of the subscriber so that it will get rendered and displayed on the UEM. So if it is perfectly displayed and rendered on the UEM, I then work on the other parts. Like, after that, based on the standard state, I have to provide what kind of percentage I have to provide for the customer in the email template. And then I work on those if and else conditions on the logics that I work based on the attributes.

I would segregate those customers who are all I want to send the personalized email. And then I used the Journey Builder to send those emails to the customers based on their purchase history. So I used the decision speed. By using the decision speed, if the customer buys something above a certain amount, they will go on a different path and get a different type of discount added on the email template. And if the customer purchases something that is below the first decision path, and it is above some given amount, they will get into a different part and get a different type of discount on the email template. And the last one is the default path. And then the third part, the customer will get a 10% discount based on the requirements, and they will get a different discount offer. This way, we can segregate those processes and messages for each customer. And other than that, we can do this thing in automation as well, like based on their customer purchase, based on their discount offers, we can segregate them by using a SQL query and create a new data extension and add those required values like subscriber key name and the previous purchase. And based on the previous purchase points or the amount they have purchased, we added the discount indirectly in that new data extension so that we can use the newly created data extensions and send the email by using the journey.

Different types of journey settings, plates, weights, engine. Different types of entry, different types of entity settings in training for, and to enter settings is, reenter anytime, reenter only after existing. The reentry is only once. Only once it will get to the attorney. It does not get into the attorney. Yeah. Reentry at one point only once will get entered the journey and does not get reentered into the journey again. Reenter anytime is that if the subscriber is already in the journey, then the subscriber key will get added into the journey again. And the third one is reenter only after existing is that the subscriber will get added to the journey only after the subscribe that is already in the process of the journey builder will get access to from the types of space. In journey, we can have decision split, random split, frequency split, engagement splits, and Einstein A/B tests. These are the splits we have. Distance speed is worked based on the decision, the rule that we have given on the split. Standard split splits the customer based on some issues like 50/50 percentage, 40/60 percentage. Based on that, we can split those customers and send them two different emails. Frequency split is based on the frequency of the email, like the open rate or the click-through behavior from the customer. Like, based on the frequency, it will get a split. Engagement split is also like the open issue under the click-through ratio based on this. The customer path will get split. What are types of waits in journey? There are wait by duration, wait until some time, wait by attribute, and normal wait.