LinkedIn Premium Recommendations for Early-Career Job Seekers
Summary
Data-driven research initiative to optimize LinkedIn Premium features, with a primary focus on attracting and retaining students and early-career job seekers, who represent the platform's second-largest user group. Leveraging surveys, interviews, and thorough data analysis, we gained valuable insights into user preferences and pain points. Utilizing this data, I delivered actionable recommendations to enhance existing LinkedIn Premium offerings and propose new features tailored to this specific demographic. The project aimed to empower students and early-career professionals by providing them with a more tailored and valuable experience on LinkedIn Premium, thus unlocking significant growth potential for the platform.
Problem Statement
LinkedIn is one of leading professional networking platform that offers trial of LinkedIn Premium. Premium has different categories, One oif which is Premium Career. The Premium Career trial provides access to various features aimed at assisting students in their employment search, including InMail for contacting recruiters and Application Insights for gaining additional information about job postings and companies. However, despite this offering, LinkedIn faces challenges with low conversion rates and low usage of Premium among students seeking employement.
LinkedIn is known to focus more on its Premium business plan than the one offered for jobseekers. Out of its 774+ million members, 39% are premium users, of which majority are businesses. (Broughton, J., 2022). However, considering that students and early career professionals form the second-largest group of LinkedIn users, understanding this segment of their users could be a great opportunity for the platform (Maciel, J., 2021).
This study aims to address this problem by understanding the requirements of this user category through data-drive approaches and recommending improvements to existing features and other suggesions that can attract and retain premium subscribers, allowing LinkedIn to increase profit pertaining to this segment.
Boundaries of the research:
The study will specifically focus on university students and their experiences with the LinkedIn Premium trial. The findings and recommendations may not be generalizable to other user segments or industries. Furthermore, the research will primarily explore factors related to features, pricing, and user expectations, without extensively delving into external market factors or economic conditions.
Method
Sample selection:
Since the study deals with improving the conversion rate of LinkedIn Premium among early-career job seekers, the target population were students and young professionals who have used LinkedIn for the job or internship search. Since we had limited timeframe and accessibility to individuals, we used non-probability convenience sampling and limited the sample to University of Washington students who fall under this category.
Data collection:
We used a combination of both qualitative and quantitative methods. We majorly relied on interviews to collect qualitative data, which was then analyzed to identify themes and trends. The primary purpose of the interviews was to understand how the participants, both Premium users and non-user, view LinkedIn Premium as a job/internship search platform, its perceived benefits and limitations, and suggestions for improvement. Since we wanted individuals to be able to freely share their experiences, we conducted standardized open-ended interviews with a pre-decided question bank for each sub-group. (Total participants: 9, Premium users: 4, Free version: 5)
To incorporate a bigger sample size, we collected quantitative data through a survey designed on Qualtrics based on the findings from the interviews. The survey served as our primary source of quantitative data. The objective of the survey was to collect data from a larger audience that could help us support or question the themes discussed in the interviews. We used it to gather data on awareness of Premium features, impact of said features in job/internship search and perceived value pricing. (Total responses: 42, Premium users: 22, Free version: 20)
Findings and Analysis
Qualitative:
Conducting thematic analysis on the interview scripts provided a comprehensive understanding of the experiences, preferences, and suggestions from students. Below are some themes that stood out.
Users:
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Use of LinkedIn Premium as a primary tool for job search and networking - "LinkedIn is my primary source for looking for internships."
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Limitations of LinkedIn Premium - "I am paying a lot to just me getting 5 inMails a month”
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Opinions on the value for money - "For the amount of money being charged on a student budget, I do not think it makes a good purchase option."
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Lack of trust - "I I feel like they're not really accurate on those algorithms."
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Suggestions for improvements - "They could include application tracking.” and “LinkedIn Premium could provide tips on profile improvement.”
Non-users:
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Lack of feature awareness - ”Since I've never used it myself, I cannot claim to know that I know all the features”
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Cost - “I think there are two main factors that have been preventing me #1 would be it's kind of expensive”
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Preference for other platforms- “And I think in general Handshake is skewed to like students. So I feel like that's better compared to LinkedIn”
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Limitations of LI Premium - “I think it will be nice if LinkedIn wants to upgrade their system like handshake like what people have applied to and like what progress is on that” (application tracking)
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A lack of trust in LI Premium - “They charge for features already available for free on other platforms”
We also found the following common themes for both the user segments:
Quantitative:
The thematic analysis of the interviews highlighted that a poor conversion rate among our target group can be attributed to user satisfaction, awareness of features and pricing. The focus of the quantitative analysis was to try find proof that either supports the findings or dismiss them.
User Satisfaction:
The data shows that 45.2% of our respondents feel that LinkedIn Premium gives candidates an advantage over other applicants, which might indicate that there is a sense of improved user-satisfaction that comes from using Premium for employment searches. However, we performed a t-test to check if there is a significant difference between satisfaction levels of Premium users and non-users for active LinkedIn users, to find that there is no statistically significant difference in satisfaction level between the 2 groups (alpha: 0.1, p-value: 0.212)
This was surprising as users are paying $30/mo for features that do not significantly contribute to their satisfaction level with the platform.
We recorded the ratings of participants for the features provided on Premium in terms of their usefulness in employement search. The thing that stood out when it comes to satisfaction is that, though not many feature rating were completely positive but, more than 75% of the participants rated the feature "Applicant Insights” average or below average, which was the most poorly rated feature.
On the other hand the feature “InMail” received around 50% positive rating, which supports our interview findings which highlighted that participants were mostly positive about InMail but dissatisfied with the limited InMail count allowed.
A chi-square test was performed for feature ratings and user satisfaction among active LinkedIn Premium users, and it revealed that there is a statistically significant association between the satisfaction levels and Applicant Insight rating, with a confidence level of 90%. This was of significance since the most of the users also rated the feature poorly, which indicates that this might be the way for improvement in user satisfaction.
Feature Awareness:
We saw significantly less awareness of features provided by LinkedIn Premium among users of the free version. Applicant Insights feature stood out, with only 35% of the non-user respondents being aware of it. Considering its association with user satisfaction, we consider it to be of potential significance.
Pricing:
100% of the respondents feel that given the features, Premium is not fairly priced. They indicate that having more advanced features would increase their willingness to pay, ie. 53.57% of the respondents did not feel that the current offerings are worth paying for but willingness to pay increased to 83.93% if new features were to be added.
The participants suggested the following new features for Premium to be worth paying for and be competitive in the market for job-hunters: Job market analytics, Personalized recommendations, Company reviews on job postings, Resume builder, Mentorship programs, Application tracking, Salary information. However, its worth noting that out of the suggested new features 5/7 is already available for free on other platforms.
Recommendations
Improvement to current features
Key findings to support recommendation:
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InMail feature is well liked by the user group
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There is a lack of trust in Applicant Insights feature
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Experience with Applicant Insight feature has a significant association with satisfaction level
InMail Limit Extension: Conditionally increasing the monthly cap on InMail messages would allow job seekers to connect with more recruiters and enhance networking opportunities.LinkedIn could evaluate the feasibility and user experience impact, implement and test within 3-6 months. We explore more on this in the coming section.
Improve Trustworthiness of Applicant Insights: LinkedIn currently relies solely on the skills section for their "top applicant" calculation. Accurately representing professional expertise in this section is crucial, but not everyone is aware of its impact. Those who optimize their skills tend to receive better recommendations. To enhance transparency, LinkedIn could improve their algorithm and provide clearer guidelines for profile optimization. (Holly Landis, 2022)
Improving features like the "Top Applicant" banner with a focus on reliability, transparency, and accuracy would increase trust in premium offerings.
Clearer marketing campaigns
Key findings to support recommendation:
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Non-users are unaware of the features offered
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Non-users are unaware of the potential benefits
For many LinkedIn users, the advantages of upgrading are murkier. They routinely receive emails urging them to upgrade—but the ongoing value of doing so is not apparent. LinkedIn could probably monetize more users if the distinctions between its free and paid offerings were clearer. (Hagiu & Rothman, 2014) This can be achieved by well crafted marketing campaigns that highlight the differences and advantages of the paid and unpaid versions.
Introduction of Student Plan
Key findings to support recommendation:
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Early career job seekers form the 2nd largest group on LinkedIn
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Users find the subscription fee to be a lot considering the features being offered
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Users are unwilling to use Premium unless they get offers
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Users would be willing to pay if provided new features
Introduce a new Premium Subscription targeting students with different Tiers. Based on the suggested new features, their availability on other platforms and audiences’ willingness to pay, we recommend the following:
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Tier 1: Current features | Cost: $10/mo
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Tier 2: Tier 1 + 5 extra InMail Credits + Resume builder, Company reviews, Application tracking, Salary
information, Job market analytics | Cost: $20/mo
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Tier 3: Tier 2 + Unlimited InMail Credits + Personalized recommendation, Mentorship programs | Cost: $30/mo
Conclusion
There are limitations of this research in terms of validity and dependability due to our sampling approach and limted time constraint. Since our sampling was based on ease of availability, it might not be a fair representation of the population. This could potentially lead to lack of diversity in the data we collected. Moreover, with the given constraints, we limited ourselves to a smaller sample size, which could impact the generalizability of our findings. The study was also conducted within a constrained time frame, which may have limited the depth and breadth of data acquisition and analysis. A prolonged duration for data collection would permit a more thorough comprehension of user experiences and preferences.
Given enough time and resources, for a large-scale research project, we would lean towards stratified random sampling and create strata based on university, academic discipline, or geographic region, as this would increase the chances of obtaining a diverse and representative sample of the entire target population. Moreover, conducting a longitudinal study might also be a good idea as it would allow for the examination of changes and trends in user perceptions and behaviors over time. This approach would provide a more nuanced understanding of how users' experiences with LinkedIn Premium evolve and enable the identification of long-term effects and outcomes.
References:
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Broughton, J. (2022, January 21). LinkedIn Facts & Statistics: 2022 Edition. LinkedIn. https://www.linkedin.com/pulse/linkedin-facts-statistics-2022-edition-/?trk=pulse-article _more-articles_related-content-card
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Maciel, J. (2021, September 7). LinkedIn for Young Professionals: Product Case Study. UX Collective.
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Holly Landis. (2022, August 19). What Does “Top Applicant” Mean on LinkedIn? TealHQ. https://www.tealhq.com/post/linkedin-top-applicant#:~:text=As%20with%20any%20algorithm%2C%20there's,feature%20will%20be%20for%20you.
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Hagiu, A., & Rothman, N. (2014, May). Making Freemium Work. Harvard Business Review. https://hbr.org/2014/05/making-freemium-work