Today on the Salesforce Admins Podcast, we talk to Kalpana Chauhan, Lead Salesforce Consultant at Mar Dat. Join us as we chat about Einstein Lead Scoring and the importance of high-quality data.
You should subscribe for the full episode, but here are a few takeaways from our conversation with Kalpana Chauhan.
Kalpana started out as a math teacher but, as her kids got older and she found herself with time on her hands, she discovered she had an affinity for Salesforce. That foundation has been incredibly helpful in her career as a Salesforce Consultant when she has to untangle something like validation rules. “Coding is easy once you understand the logic and flowchart of how it actually works,” she says.
Flows and automation have always held a special place in Kalpana’s heart. There is so much manual work that you can make unnecessary if you’re willing to sit down and thoughtfully analyze a business process. And new tools like Einstein are making that easier than ever before.
One of Kalpana’s clients needed help resolving issues related to proper lead qualification and marketing engagement. “The marketing team was eager to enhance their engagement with leads, while the sales team was seeking better clarity regarding which leads were sales-qualified so they could focus their efforts on conversion,” she says.
That’s when Einstein came to the rescue. They worked through the AI Wizard and came up with three scores:
Together, these scores helped marketing engage prospects at the right cadence while sales could pursue an optimal nurturing and conversion strategy for each lead.
If you want to start using Einstein in your org, Kalpana recommends starting by taking a close look at your data quality. “Data is the key,” she says, “the more data you feed in, the more accurate your results will be.” That means Implementing solid data validation rules and using screen flows to remove duplicate records.
Getting up-to-speed on Einstein was easy with all of the resources out there from Salesforce. In addition to Trailhead, Kalpana found Bootcamps to be especially useful. “I love anything with visuals,” she says. She also recommends going to your local Trailblazer Community Group meeting to connect with other admins facing similar challenges.
Be sure to listen to the full episode to learn more about Einstein, email marketing, and data cleanup.
Mike Gerholdt:
This week on the Salesforce Admins Podcast, we’re talking with Kalpana Chauhan about building flows, Einstein, and even some mathematics. So Kalpana built some really cool stuff with Einstein in Flows recently, so wanted to share that. Plus you guys is a really fun story. Started off learning math, which, man.
Before we get into that episode, just want to make sure that you’re following the Salesforce Admins Podcast on iTunes or Spotify. Shout out to the Spotify listeners, or wherever you get podcasts. Te reason I bring that up is then you don’t have to think about like, oh, is there a new episode? Do I got to refresh it? What do I got to do? How do I get the episode on? Is this the latest thing? Am I four behind? Nope. If you’re following it, the newest stuff just drops right onto your phone as soon as it comes out every Thursday morning. It’s like magic. So with that, let’s get to our conversation with Kalpana.
So Kalpana, welcome to the podcast.
Kalpana Chauhan:
Thanks for inviting me, Mike. It’s a pleasure to be here.
Mike Gerholdt:
Yeah, it’s great. Well, let’s get started with how you got started in the Salesforce ecosystem and some of what you do.
Kalpana Chauhan:
Absolutely. So I can say I’m a good example of how one can make an exciting career shift into the amazing world of Salesforce. So after finishing my college and diving into family life, I focused on a few things that kept me going, and I think one was mathematics. I love math, and that inspired me to teach young students in the field. Of course, I was busy raising a family, but when my kids grew bit older, I had a lot of time. Then I got interested in web development. That time I didn’t have any idea that eventually it’ll bring me into the amazing world of Salesforce.
I can tell you that was the best thing happened to me learning the whole Salesforce ecosystem. I completely fell in love with the Trailhead. I earned points, badges, and I did a lot of projects, and in no time I reached the ranger level. Through the Salesforce community feed, I met Lo. She’s the Salesforce partner and CEO of Mar’s Art. In Lo, I found a mentor who in encouraged and supported my learning journey. She was always inspiring and I’m really grateful for the opportunity to learn and grow under her guidance. Here I think it’s been an amazing journey and I can’t wait to share my insights and experiences with you today.
Mike Gerholdt:
Yeah. No, it’s great. Boy, I wouldn’t have guessed math. One thing that never stuck in my head was math. Do you find you do a lot of math with Salesforce? Let me rephrase that. Are a lot of the concepts of math applicable to validation rules and stuff like that?
Kalpana Chauhan:
Absolutely. So-
Mike Gerholdt:
Yeah?
Kalpana Chauhan:
Oh, yeah. I love math. I think it’s the logic or you can say the problem solving skill, that is something if you’re doing Flows or the way you said validation rules, it’s very easy to understand. I think coding is very easy once you understand the logic, the flow chart, how it actually works.
Mike Gerholdt:
Yeah, I suppose that’s probably… I didn’t get math, so coding is a little bit harder for me. It’s always those and/or statements.
Kalpana Chauhan:
Absolutely. One thing what I like about Salesforce is if you are not good at coding, then also you’re good.
Mike Gerholdt:
Yeah. Proof positive is me. I’ve spent my whole career, I’ve never deployed a line of code at least unless it was in an app exchange package and they snuck it in on me, that would be the only way you could sneak through code on me. Yeah, I love, there’s a ton of different ways for us to configure the tool in a way that makes it very approachable and friendly.
You transitioned and learned a lot of math and now you’re doing a lot of cool stuff. What are some of the things that you’re working on that maybe other admins would find interesting?
Kalpana Chauhan:
Oh, that’s interesting question. So I used to work for the healthcare and there they had the primary challenge that they were shortage of the provider reference. In their own words, they said that getting calls from the provider was a game changer for them and lack of provider reference was significant impacting their businesses. After going through their data, we understood that the issues related to proper lead qualification and email engagement. The marketing team was eager to enhance the engagement with leads, while the sales team was seeking better clarity from the marketing regarding which leads were sales qualified. So allowing them to concentrate their efforts on the conversion.
Mike Gerholdt:
Yeah, there’s always… Interestingly enough, I had a lunch with an admin right before Midwest Dreamin and they were also in the healthcare space. It’s funny, you talk with admins in some of those very specific industry verticals, and while the challenges are always the same, it’s just the way that you have to solve them are always super unique for that one particular institution or organization that doesn’t seem to apply. You’d think patient intake’s the same across the board, but in fact some of the stuff that you have to do is also very different.
Kalpana Chauhan:
Absolutely.
Mike Gerholdt:
So working through looking at mathematics and some of that stuff, what parts of the platform naturally made sense to you and that you found were easy to pick up right away?
Kalpana Chauhan:
I think initially I was working as an admin, and slowly and slowly, I started liking digital marketing, email marketing. That’s how I ended up in Pardot and Marketing Cloud and DemandGen. So this is my little transition from the admin to the digital marketing and email marketing. What I liked the most in admin was the Flows. I like the automation. There should be less manual work, more of automation. No one has to do a lot of enter manual things.
Mike Gerholdt:
Yeah, I would agree. Going back to the early days when I started at Salesforce, we had Workflows. They still exist, but the feeling of making something update when a user does something else or verifying that, it feels very powerful. I look at the amount of things that we can do now with Flows.
I know one of the things I enjoy building is screen flows. Do you find building screen flows more applicable to a lot of the things that you’re working on as opposed to maybe a record triggered flow? Or are there some that you navigate towards a little bit more naturally?
Kalpana Chauhan:
I think the record triggering flow, that is something I use quite often and that’s what I like a lot, because if you are in a, say, sales process, that’s the time when you use the flow a lot. So if I say any stage has changed and there is so many people in the sales team. If stages has changed, few people, they’ll be interested to get the notification so that they can keep the track what is happening and they can start with the next process. Notifications, if stages changes, this notifications should go this person. If it is changing to the other, then the notification should go to the other person. Another thing, what I liked was I implemented the band score.
Mike Gerholdt:
Tell me more.
Kalpana Chauhan:
Yeah. So that is something like custom metadata type, it’s like budget analysis. So every question has four set of answers, and if you are having a conversation with the potential clients and then you get more clarity, more understanding if this is a fit prospect or not.
Mike Gerholdt:
Was the organization giving you those ideal outcomes as a way to score that or were you using some sort of AI or some sort of learning model?
Kalpana Chauhan:
We were using the standard, which is provided by the Salesforce. Generally we go with that out of the box functionality, but of course you can do customly. You can do the way you want, but right now we are using out of the box. Einstein is something that I used with the healthcare that was the must tool.
Mike Gerholdt:
Okay. How so?
Kalpana Chauhan:
I can say Einstein was to the rescue. So when it came to improving the provider referrals and email engagement, that’s how we came for the Salesforce Einstein, the AI. So we came up with the Einstein behavior score, Einstein engagement frequency, and Einstein sent them optimization. These were the three Einstein features we used.
So the number one was very good Einstein behavior score, because the product lead score out of the box, that’s not that effective when it compared to Einstein behavior score, because the Salesforce automatically calculates a lead score based on the provider engagement behavior. Based on these scores, we scored them in three categories, say hot, warm, and cold. Then we use this for the segmentation to tailor our nurturing and conversion strategies.
So this was the number one Einstein behavior score, and the second one was the Einstein engagement frequency. This one was a game changer, because when you’re doing regular email marketing, you want to know that if you are flooding others’ inbox with emails or you are sending them under it. So that’s how Einstein engagement frequency, it strikes the right balance for the email marketing efforts. So it help us to figure out if this provider is getting a lot of emails or these are the ones which are getting not enough.
The third one was the Einstein send time optimization. It automated the timing of our email sends, because not everyone will open their email on Monday. Sometime people will open on Tuesday or they open in the afternoon time. So what it does is it studies your historical engagement pattern and it sends exactly at that time, that day and that time. So these three features were very helpful and these were our trusted companions in navigating the complexity of lead management and email marketing. I think they were very, very effective.
Mike Gerholdt:
Yeah. No, that’s always the stuff that people are working on. Did you use a lot of Trailhead modules to get up to speed with Einstein?
Kalpana Chauhan:
Yeah, of course. Not only that, I also watch the boot camps.
Mike Gerholdt:
Oh.
Kalpana Chauhan:
Yeah. Those are very informative. Doing the Trailhead is also very good, but boot camps are like… Any visual, I love it.
Mike Gerholdt:
Yeah. I completely understand. Now, let’s see, you’re based in the East coast. Do you have a lot of Salesforce user groups around you there that you get to be involved in as well?
Kalpana Chauhan:
Yeah. Of course. Yes.
Mike Gerholdt:
I’m sure there’s quite a few.
Kalpana Chauhan:
Yeah, I think it’s everywhere now.
Mike Gerholdt:
Yeah. No, it’s good. Those are also really good ways to sit down and work through different issues and ask business problems, especially if you’re trying to work through some scoring thing, which again, comes back to math. Always comes back to math.
Kalpana Chauhan:
Yeah, absolutely.
Mike Gerholdt:
As we wrap things up here, if you are a newer admin getting started with some of the Einstein stuff, obviously go to your user group. Is there any suggestions you’d have or tips that helped you understand some of the things that you are building?
Kalpana Chauhan:
Yeah, absolutely. What I will say is I think data is the key, because Einstein works well when you have a lot of, say, historical data, minimum six months to one year. The more data you feed in, the more accurate and good results will be. So I think any admin, they should work more on the data to analyze and understand what will work best for you.
Mike Gerholdt:
Yeah. No, I completely… Also back to your mathematics background, the validation rules help keep good data. That way you’re making sure that there’s actually a phone number in a phone number field, as opposed to just call notes or something crazy like that.
Kalpana Chauhan:
Absolutely. I can tell you that. I can give you examples, because when we worked for the healthcare, data quality was the issue, the biggest issue. So there was so many duplicates provider were there an data was not up to date. Because there were so many providers, they were not working, but their data was there. Then earlier they did not use the validation rules. For an example, they were filled. A primary email should be their business email, but there were no validations or nothing. So people were putting their personal email, you know what mean?
Mike Gerholdt:
Oh, no.
Kalpana Chauhan:
Yeah. When you’re doing email marketing, then you’re not getting their emails, because they have not used the proper email. So I think validation tools is something very, very important, and as an admin, we use a lot. Same way like Flow. So I think for deduplication, I created a simple Flows. So if anyone wants also they cannot create duplicate contact.
Mike Gerholdt:
Well, that’s also very good. There’s a lot to be said about creating a screen flow that would loop through your records and make sure that that person does exist or doesn’t exist, and making sure that data is clean. Because as we’ll see, the best data is the stuff that Einstein and AI can really ingest and give you the best quality score too. I’m sure you saw that when you were building your different Einstein scores.
Kalpana Chauhan:
Yeah, absolutely. So the first and foremost thing was to clean the data. Then only everything will work well.
Mike Gerholdt:
Yeah. Well, it’s like a house. It’s always a lot easier to just start with a clean house before you do anything, as opposed to a messy house because then it feels like you’re always fixing things.
Kalpana Chauhan:
Yeah, that’s important.
Mike Gerholdt:
Absolutely. Well, Kalpana, thank you so much for coming on the podcast to talk about this. I learned a lot about math and Einstein and Flows, and it was really great discussion.
Kalpana Chauhan:
Thank you so much for having me, Mike.
Mike Gerholdt:
That was a fun discussion with Kalpana. She lives out east and of course this time of year in October, it’s probably really beautiful with the leaves turning and stuff like that. Math, probably my biggest hurdle in life is learning math. I’m glad there are people out there Kalpana that know math to build really good validation rules.
Now, if you enjoyed this episode, I need you to do me a favor. Just share it with one person. Now you can go above and beyond, share it with two. You can be a rockstar, share it with three. To do that, if you’re listening on iTunes, all you got to do is just tap the dots. There’s three dots you choose share episode, and then you can post it on social. You can text it to a friend. You can be like, “Hey friend, you’re good at math. You could do Salesforce too and be like, Kalpana.”
If you’re looking for more great resources, your one stop for everything Salesforce admin is say it with me, admin.salesforce.com, including a transcript of the show. Of course, be sure to join our conversation, the Admin Trailblazer group. That is in the Trailblazer community. Don’t worry, the links to all of that are in the show notes. So until next week, we’ll see you in the cloud.
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