Onboarding project | Sprinklr
💡What is Sprinklr?
Sprinklr helps social media teams manage brand engagement on social at scale, no matter the channel. It does so by unifying listening, engagement, advertising, customer service and reporting on a single, AI-powered platform. Social media teams can leverage AI to unearth trends, engage faster, boost reach, and address customer issues while maximising productivity and mitigating brand risk across 30+ channels.
Which Product are we considering here?
We will be going through Sprinklr Social’s self-service version -Social Advance-, which has a simpler UI, out-of-the-box listening and OpenAI’s GPT integration. It is perfect for smaller teams looking to listen, publish, engage and analyse with ease.
Sprinklr's Brand Promise and Feature Deep Dive: Sprinklr Feature Deep Dive.pdf
🥋Ideal Customer Profile:
Identified Company Profile:
Feature
Industry
Marketing Team Size
Company Budget
Marketing Budget
Social Media Presence
General Problem Statement
Startups / SME
Any
3-50
$10M - $250M
$30K - $1M
3+ Accounts
- Need a simple tool to Publish across major social channels. Since the product offering is simple, a tool which can get started quickly would be effective.
- Platform to manage inbound social messages and engage with them across multiple channels
- Understand customer behaviour and compare social performance with competitors
- Tool that can scale easily
Let's Take a look at our ICPs and what is the Job to be done:
Majorly all the personas have Primary functional goals and secondary financial goals.
Meet - Anna Lee, Social Media Manager
Meet: Camila Jhonson, Brand Manager
Meet: John Howard, Content Publisher
Meet: Jacob Frost, Community Manager
Meet: David Choe, Engagement Agent
Meet: Kayla Jacob, Analyst
🔑 Onboarding Teardown:
Step-by-step walkthrough and analysis of Sprinklr onboarding:
⌚️Activation Metrics:
When can a user be called an active user?
Metric #1:
The number of team members added
Hypothesis:
3 users were added in 7 days
Details:
When a user invites other team members to the platform they are staking their reputation for the product. Hence, users would invite team members only when they are confident about the product. The higher number of team members creates a data hook where it becomes more difficult for the entire team to switch platforms once everyone has adopted the same.
Metric #2:
Number of Post Omni published
Hypothesis:
5 posts were scheduled in 1 week
Details:
Companies usually have monthly content planned, and the platform is majorly used to plan and schedule content. Having to schedule 5 posts over 5 platforms means 25 posts to be manually published to each account without a platform, but with Sprinklr users will only have to publish 5 posts which makes the process more efficient for them and get hooked on the platform.
Metric #3:
Number of rules configured in the System
Hypothesis:
3 Rules were configured in 2 weeks
Details:
Usually, users configure 3 types of rules: Rules for approvals of the posts/assets, for tagging posts and for tagging incoming messages. Once these rules are created rules create process efficiency to save time or reduce the efforts of the users to do manual tasks, making the platform more usable and sticky
Metric #4:
Custom report or custom metric request / Generates presentation out of reporting
Hypothesis:
Sprinklr receives a request for a custom metric or custom report from a user or the user creates a presentation out of the report in the first 30 days
Details:
I am skipping time spent as a metric to get more granular and identify the actual sticky points in the user journey. If a user has requested to create a custom reporting setup the user is prepared to make efforts to reach out to Sprinklr for the same given that it is not upfront possible in Sprinklr, or the user generates a presentation out of a report that means the report is useful for the user and is getting shared across other stakeholders
Metric #5:
Number of tasks completed in a month
Hypothesis:
10 Tasks completed in 30 days
Details:
If the customer is using the platform to close a large number of tickets it implies they have set up their account and performing multiple activities like post creation/ approval/ replying to messages and others in the platform. It is a clear indicator that users are finding the value out of the product.
🧭 Metrics to be tracked:
- Total users opting for a free trial
- Total users adding details/ connecting account
- Total users Inviting a team member
- Total users adding accounts
- D30, D60, D90 Retention
- MAU
- Free Signup vs Subscription rate
- Onboarding completion percentage and time.
- Publishing adoption = (volume of posts published from the Platform/ total volume of posts)*100
- Engagement adoption = (volume of reactive messages published from the Platform/ total volume of reactive messages)*100
- Number of topics created
- #times the quick search is used
- Number of deep insights created
- Number of assets added
- Adoption Funnel
- Total users booking sessions with Sprinklr vs Total converts
- Time spent on the platform
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