Introduction

In the Acquisition project, it was identified that the topic of data security & privacy was a largely untouched market in India compared to USA & especially the EU. Consumers across various markets have an increasing internet presence, footprint and engagement, with

• 83% of internet users concerned about their online privacy but no solutions available for consumers in the market
• Only 15% of internet users were aware of data protection laws & regulations in India
• 29% of internet users trust companies with their personal data.

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With this, the core value proposition to that is intended to be offered with the Norton 360 Deluxe plan is: 💡 Providing device personal & online protection from Privacy & Identity threats.

Features of the product

​The features that are available (and publicly marketed) with the products are:

NOTE: The onboarding project only includes the package Norton 360 Deluxe available in the website.

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Next, lets look at the ICPs that we had decided to acquire from the Acquisition project:

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Jobs To Be Done

Objective from the following exercise:

1. Identify the core JTBD for each ICP based on their pain points, goals and how Norton is meeting them
2. Based on user interviews, finalize the core Job that the product should/could be built around -
3. 1. there should be relevancy/affinity from ALL ICP to this core job.

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How was the below framework decided?

1. Outside-in approach: Capture insights on recent innovations, accomplishments, solutions in the same + adjacent industry as Norton
2. The list of potential “consumer jobs” was by co-relating the primary pain points, goals from the ICP research done during Acquisition
3. 1. This also includes user feedback from 2 people based on the onboarding video I took (of myself onboarding into the product from different devices) & the features offered.
4. Affinity rating was by co-relating the jobs that was narrowed down + what Norton had to offer
5. Opportunity scoring is based on what Norton has vs. competitors providing similar solutions.

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Auxiliary insights on the ICPs captured during Acquisition for additional context:

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• Over 10 people across both age groups had some knowledge of what data breaches are and specific, potential ramifications.
• • People in the 35-44 age group had lesser knowledge than age group 25-44.
• All (10) of the users, across both age groups, who had some knowledge of what data breaches are were aware of atleast 2 incidents of data breaches specific to India in the last 5 years.
• • 8 of them THOUGHT they were victims only because they have received alot of cold calls/spams but don’t use a software to be sure.1 person uses a software that gives them that insight.
• 8/12 people were “Somewhat concerned” about online threats.
• • 3 of them were “Very concerned”.
• People in the 25-44 age group think that Antivirus is not a primary need anymore since it is provided/solved by the ecosystem it is used in. (Apple, Windows defender)

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So, WHAT is the core Job To Be Done that Norton needs to achieve to meet the expectations of these ICPs?

Ancillary Jobs To Be Done for each of the key features prioritized:

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Activation Metrics

Hypothesis 1

We believe that promoting the top 3 desired features of Norton 360 Deluxe (Dark Web Monitoring, Password Manager, Parental control per acquisition strategy) converts as many, or more, landing page visitors as promoting the full feature set (per paid ads active in India, from acquisition project)
To verify this we will create 2 variations of the Norton 360 Deluxe plan page that will highlight either Dark Web Monitoring, Parental Control or Password Manager, based on the source they arrived from and THEN list the rest of the other features offered. In all of the cases, the user will end up with the same product at the same price.
and measure Conversion rate, Customer Acquisition Cost, Cost Per Click, Cost Per Acquisition, feature setup/adoption (of password manager or dark web monitoring)
We are right if Conversion rate stays the same as the full-feature list store page that is already being advertised or is less then X% and if the customer either sets up password manager or dark web monitoring (based on the ad) within 7 days of purchasing the product.

Hypothesis 2

We believe that notifying users about whether their email was breached or not will help them feel more protected, and lead to higher engagement.

To verify this we will automatically onboard their registered email address into Dark Web Monitoring when they first sign in to the app and alert them in-app & with an email with details of the breach, if applicable, or that there was no breach, demonstrating that there is ongoing monitoring of their email

and measure the CTR on these alerts (by email & in-app alerts), their consumption of the “what to do next” article, # of sign ins post purchase, how many breaches the customer got.

We are right if the CTR on these notifications is X% within 24 hours of first sign-in, and if there is a breach the “what to do next” article is read the user within 3 days of first sign in.

Hypothesis 3

We believe that reminding customers that their product has coverage for more than one device will help them realize the value of their purchase.
To verify this we will provide them an option to setup their product on another device immediately after the product is setup and signed in AND have an easily accessible option to install on another device. This is by providing an option to scan a QR code for a mobile, text it to a phone number, email it to an email address or copy the installation link to send it by WhatsApp
and measure whether this happens immediately after setup/sometime after setup (through the in-app option), type of device first setup with, type of >2nd that was setup and the method used to setup other device(s).
We are right if there are +/=2 devices from the subscription that the product is installed in within 7 days of first sign-in. Stretch goal: X% of subscribers that installed on a PC have atleast one mobile device protected.

Hypothesis 4

We believe that users will be more engaging with the app when they effortlessly find the “Non-Antivirus” features that they are eligible for, that satisfies their core protection need & builds trust.
To verify this we will inform them what features, especially highlighting the Non-Antivirus features as the application is being installed/setup and once its setup, highlight Dark web Monitoring, Password Manager, Parental Setup, Cloud Storage, Safe search for the customer to setup/engage with, describing if they are already setup or not
and measure how many of these features are setup and when, how many times an user uses the feature, how many devices they use it in, what type of device they use it in.
We are right if there are +/=2 Non-Antivirus features the customer has setup within 7 days and atleast one Non-Antivirus feature is used every day for the next 23 days.

Hypothesis 5

We believe that users will be more engaging in a mobile app (Android & iOS) vs. Desktop/Macbook/Web since their core jobs to be done can easily be accessible form factor + the persistent usage of mobile devices.
To verify this we will allow free mobile users organically installing the app from the play/app store to scan any email address in the Dark Web before offering them to purchase a plan. We will also limit every engagement of Dark Web Monitoring, Password Manager, Parental Control within one single app across both iOS & Android
and measure what % of these features are used in mobile vs. web vs. desktop, how many times an user performs a particular task in each of these features in mobile vs. web vs. desktop
We are right if mobile apps (Android, iOS) have X% more engagement (as defined above) for all of the features compared to desktop/web within the first 15 days of first sign-in.

Hypothesis 6

We believe that users who add more PII data types for the Dark Web Monitoring feature to monitor will realize greater value & powerful from the tool and feel more confident that Norton ”has their back”. To verify this we will in addition to the registered email address auto-monitored, inform users post sign in through email & in-app messages that there are other data types they can monitor (and listing them out), with a CTA that directly deep-links them to the feature screen
and measure how many data types are monitored and within how long post sign in, what data types, CTR of email vs. in-app message, if the customer read the “what to do next” article for the respective data type.
We are right if the customer monitors +/=2 data types from phone number, insurance, Gamer tag, credit/debit card within 5 days of first sign-in.

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Onboarding Teardown

Onboarding teardown- Norton.pdf

Metrics to track

• [ ] DAU/MAU of active users
• • [ ] Active users are paid customers who have Norton installed on =/+2 devices, setup atleast 2 features, app opens every 48 hours
• [ ] # active sessions (see above for definition of “Active”
• [ ] Retention rate
• • [ ] D1, D7, D30
  • [ ] Engagement vs. Retention
• [ ] Time user spent on the app by device type
• [ ] Time taken for users to discover each feature by device type
• [ ] Average time spent on each screen for Dark Web Monitoring
• [ ] Customer journey & drop outs
• [ ] Play/App store feedback (Qualitative)
• [ ] PlayApp store rating
• [ ] App open rate
• • [ ] Organic, by device
  • [ ] Per feature alerts, by device - what feature, what was the alert, customer journey
• [ ] Customer support
• • [ ] Time range of first sign in + 7, 15, 30, 60… days
  • [ ] # of tickets for each feature
  • [ ] What are they saying for each feature?
  • [ ] CSAT for each feature
  • [ ] What KB articles have they visited for each feature?
  • [ ] If there is a chatbot, what queries for each feature?
  • [ ] Cost per each call/chat
• [ ] On store landing page (Acquisition source)
• • [ ] CVR, CAC, CPC, CPA
• [ ] CTR of in-app alerts
• [ ] Email open rate (by emails)
• [ ] Consumption of feature
• • [ ] which feature was setup
  • [ ] Which feature did they start to setup and dropped
  • [ ] Which device are they using it most in
• [ ] Avg number of breaches per customer by data type
• • [ ] % who “completed” the next steps provided
• [ ] Number of devices per subscription
• • [ ] Device types
  • [ ] Time taken to setup
  • [ ] Most common method to setup
• [ ] User cohorts - for activation metrics
• [ ] Product CSAT/NPS
• [ ] Feature CSAT/NPS
• • [ ] Survey when customers complete a “Task” from Activation hypotheses

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