2 Shabd Reviews vs LinkedIn Recommendations

• by 2 Shabd
• September 18, 2026
• 5 min read

In this blog, we discuss how 2 Shabd reviews are not the same as LinkedIn recommendations.

LinkedIn Recommendations were created to add credibility to a professional profile through what other people say about you. But recommendations have a fundamental limitation: they are testimonials, not a structured record of behaviour. People naturally tend to give positive recommendations, recipients control what remains visible, and each recommendation exists largely on its own. 2 Shabd approaches the problem differently—by turning repeated observations from real experiences into a structured behavioural picture that can include both strengths and areas for growth.

1. LinkedIn Recommendations Have a Positive-Only Selection Bias

A LinkedIn recommendation is usually written because someone wants to recommend you. If the recommendation contains a serious negative trait, the recipient can simply choose not to display it.

The result is predictable: a profile visitor mostly sees positive testimonials.

That creates a selection bias. A person may have weaknesses that repeatedly appear in their interactions, but those weaknesses rarely make it onto their public LinkedIn profile.

2 Shabd handles negative feedback differently.

A user can accept a negative review and keep it within their inner circle rather than making it public. At the same time, repeated negative observations can contribute to Growth Areas, giving the user a private view of traits they may need to improve.

Even the decision to reject reviews is not invisible. It contributes to the user's Review Acceptance Rate (RAR).

So instead of:

“Show me what people say when they recommend you.”

the model becomes:

“Show me what people consistently observe about you with review visibility filters from Public to Outer Circle to Inner Circle.”

2. LinkedIn Recommendations Are Isolated Compliments. 2 Shabd Looks for Patterns.

Consider a LinkedIn profile with 15 recommendations:

“Great leader.” “Excellent communicator.” “Very hardworking.” “Pleasure to work with.” “Great team player.”

People can independently describe different situations in which the same behavioural trait appears, the useful information isn't the 15 paragraphs.

The useful information is the pattern hidden inside those paragraphs.

And of course, these statements may all be genuine. But a visitor still has to read through them and mentally figure out what the common pattern is.

Most profile visitors won't do that. Therefore, it is safe to say that LinkedIn primarily gives you the testimonials.

2 Shabd is attempting to extract the behavioural meaning from them by changing the unit of information from the individual review to the behavioural pattern.

Instead of asking the visitor to read 20 separate reviews, 2 Shabd can summarize observations from different events and identify recurring traits.

For example:

• Communication: observed repeatedly across 4 events
• Leadership: observed in 3 events
• Initiative: observed in 5 events
• Conflict handling: growth area (confidential to the user)

The important difference isn't simply that there are more reviews.

It is that multiple observations become one understandable picture.

3. LinkedIn Recommendations Are Usually Event-Endorsements. 2 Shabd Is Becoming a Continuous Record.

A LinkedIn recommendation is typically associated with the end of a relationship or experience—a job, internship, project, or academic period.

Once that recommendation is written, it largely stays there.

2 Shabd is built around repeated observation.

A student can receive reviews after one college event, another project, an internship-related activity, a competition, or another independently organized experience.

This creates something LinkedIn recommendations generally don't provide:

a behavioural timeline.

The question changes from:

“What did someone say about me after one experience?”

to:

“What have people consistently observed about me across different experiences?”

That distinction becomes particularly important for students, because a single recommendation cannot establish whether a trait is temporary or consistent.

4. A LinkedIn Recommendation Can Come From a Senior Person Without Proving What Happened.

The authority of the person writing a recommendation can make it appear credible.

A recommendation from a CEO, manager, professor, or senior executive certainly carries context.

But the recommendation itself doesn't independently establish that the described behaviour actually occurred.

2 Shabd is attempting to introduce verification around the observation itself, rather than relying solely on the status of the reviewer.

1. For organized 2 Shabd events, the student's actual work is publicly presented—for example, through an Instagram Reel—so there is an observable output associated with the review.
2. Each review is written by verified profiles and contains 1 to 10 users as witnesses to the event.
3. The behavioural assessment then go through a final layer involving a certified psychologist who assigns the final trait.

The distinction is:

LinkedIn: Who is recommending you?

2 Shabd: What did you actually do, and what behaviour can be established from it?

That moves credibility away from title alone and toward evidence + assessment.

Conclusion

LinkedIn Recommendations established the idea that other people's experiences can strengthen a professional profile. But the traditional recommendation model is still largely based on positive, isolated testimonials.

2 Shabd is built around a different premise:

One review is an opinion. Repeated observations can reveal a pattern.

By allowing accepted negative feedback to contribute to private Growth Areas, collecting observations across multiple experiences, and adding verification around the work and behavioural assessment, 2 Shabd aims to move professional reviews from testimonials toward behavioural evidence.

The difference is ultimately simple:

LinkedIn Recommendations tell people what others said about you.

2 Shabd aims to extract verified pattern from what people consistently observed about you.