Klout score

Klout was an early attempt to answer an appealing but difficult question: how influential is a person or organisation across social media? The service converted activity and audience reactions from several networks into a score from 1 to 100. Klout closed in twenty eighteen, so its score is no longer a usable KPI. It remains valuable as a case study in the promise and danger of proprietary composite metrics.

When to use it

Use this article for historical analysis, metric design and critical discussion—not as a recommendation to collect a current Klout score. It is useful when:

• examining the evolution of social-media measurement;
• designing a replacement influence or advocacy KPI;
• evaluating a metric whose formula is proprietary;
• discussing whether unlike forms of engagement can be combined into one score; or
• teaching the difference between reach, engagement and influence.

Origins

Joe Fernandez and Binh Tran founded Klout in two thousand and eight. The company developed a proprietary score intended to estimate online influence from the size of a user’s network and the reactions generated by that user’s content. Lithium Technologies acquired Klout in twenty fourteen and discontinued the standalone service on twenty-five May twenty eighteen. Any reference to Klout as an available measurement service is therefore historical.

What it is

Perspective: Marketing and sales.

Historical performance question: To what extent does an account influence the behaviour of its online audience?

Klout assigned individuals and brands a score from 1 to 100. A higher score was intended to indicate a greater capacity to prompt reactions and propagate messages across connected social platforms. The service’s methodology changed over time as networks and available data changed.

An early version of the model described three components:

True Reach:

the estimated size of the audience that actively engaged with the account, rather than the raw number of followers or connections;

Amplification:

the likelihood that published content would generate reactions such as replies, shares, likes or comments; and

Network influence:

the estimated influence of the people who engaged with the account.

Klout did not disclose enough of its weighting and transformation logic for an independent analyst to reproduce the score. That opacity was a central limitation: a movement in the headline number could not always be traced to a specific audience behaviour, platform change or methodological revision.

How to use it

Measurement

Klout historically attempted to represent online influence as a composite score; today it is best treated as a case study rather than a live measure.

Data collection method

The service collected account, network, publishing and engagement data from supported social platforms connected by the user.

Formula

The exact calculation and component weights were proprietary, so an independent analyst could not reproduce the result.

Frequency

The service refreshed scores as its available platform data and scoring model changed.

Source of the data

Inputs came from the social networks and accounts supported by Klout at the time of measurement.

Cost/effort in collecting the data

Connecting an account was simple for the user, but the opaque processing made validation and diagnosis difficult.

Target setting/benchmarks

Historical scores are not stable contemporary benchmarks. A replacement scorecard should set transparent targets for its individual components and verified outcomes.

Example