Predict the future of recruitment based on the internet ecosystem

I myself had worked in the internet advertising industry for long. Perhaps, this is the reason why I always try to understand the recruitment process like ads. This is interesting because we can find many common points between ads and recruitment actually. However, I have not compared and analyzed both history and process seriously yet. In this blog, I'd like to try to predict the future of recruitment process based on the ecosystem of internet ads.

About the history and the ecosystem of internet ads, I refer DSP/RTBオーディエンスターゲティング入門 (a book about DSP/RTB written in Japanese).

Comparison between ads and recruitment

The reason why I can say the recruitment and the ads are similar is both are the communication between a company and people. Communication is composed of the stakeholders and process.

The above figure shows the stakeholders related to ads. In the recruitment, Media is equal to Recruitment channel, Client is equal to a company where is looking for candidates, User is equal to a job seeker. About the process, I'll describe later.

Comparison of the history of ads and recruitment

In order to see the common points between ads and recruitment in the other viewpoint, I'd like to review the history of internet ads here. Then I tried to match with recruitment.

History of ads

Approximately, the history of internet ads has advanced from Space, Demographic to Person. In the first phase of ads, media just provided the ad spaces and they published the static banner images. After that, some services which can target certain demographic (a group of persons) were provided. Recently, in order to increase the effect of ads more, most of the clients or ad agencies use RTB (and actually DMP together, which I'll describe later) and it enabled us to target the most effective person to show the ads.

History of recruitment

In compared with the history of the recruitment, the first era was job ads on paper, and I must say this way is almost not possible to target demographic or person. The next phase is web job media. This is also difficult to target. But after that, some services started using SNS or AI to improve the accuracy of matching between companies and job seekers. So recruitment industry is also getting closer to a Person. But it's just the beginning in compare with the internet ad industry.

In the viewpoint of optimization to a person, internet ad industry is going forward as a service and I think more services related to recruitment will be provided to for optimized matching between a company and a person.

Communication on ads

Funnel of Attention, Interest, and Action

In the ad industry, in general, it is said that the communication with users is like above. The steps are:

1. Let people who don't know of a product (which a client wants to promote) know.
2. Let people who know (or have just known) have interest.
3. Let people who have interest act (purchase).
4. Get the attention of people who are similar to a person who acted (Look-alike).

This communication flow is defined in detail as AISAS like below. This stands for Attention-Interest-Search-Action-Share.

AISAS theory

For example, company A wants to promote a cosmetics X. The typical behavior from Attention to Share is like this.

1. First of all, a person (let's say Ms.B here) knows the existence of its product on TV CM or pure ads on some big media.
2. After that, she knows the concrete efficacy, benefits and so on the retargeting ads or DSP with high frequency. 
3. After her interest in its product increased enough, she searches by product name on Google, then she will find a product page or landing page.
4. On its website, she purchases its product.
5. After its product is delivered, she may share the photo on Instagram. If the effect is very good and she is satisfied with the effect, she may share the review on Facebook.

In step 4, media can get the information of persons who purchase the cosmetics X. Then they can know what kind of demographic has high possibility to purchase. Using this data, they can get more Attentions with more specific conditions.

How about AISAS in recruitment?

Now, let's replace this flow with recruitment case.

1. [Attention] In order to let people who don't know of a company or its recruitment activities know, a company uses .... what? They sometimes can use job fair, PR and so on but it's a little hard to reach to mass.
2. [Interest] In order to let people who know (or have just known) have interest in a company, what kind of method they can use with optimum frequency? SNS is one of a good way but it's a little hard to control the frequency (in general, it is said people feel bored if they see the same contents over 30 times and they will lose the interest) and optimum contents for each person.
3. [Search] In order to let people who have interest act (apply), a company basically use web job media or application form of a corporate site.
4. [Action] After some selections, you may join a new company.
5. [Share] After you join a new company, you share on SNS...? You may change the profile on Facebook or LinkedIn but I'm not sure it's typical behavior of majority and not sure it can get more Attentions.
6. [Look-alike] Is there any service to get more Attentions with more specific demographic using the Action data retrieved in Step 4?

Through this article, I conclude that companies should need the services for Attention, Interest, Share and Look-alike phase in the recruitment process.

The ecosystem of internet ads

Internet ad industry has the ecosystem to realize ads optimized for users. I don't describe the detail here but what I want to say is the ecosystem is commoditized and there are lots of players. This is called chaos map and actually, there are more players in this industry (the above diagram is the very simplified one).

Try to apply the players of recruitment in the ecosystem of Internet ad

There are may chaos map of HR tech already but I tried to apply the players of recruitment services to the players of Internet ad ecosystem in order to know the optimization to users (job seekers).

As far as I compare like above, I can conclude about recruitment like below.

• Not many opportunities or services to get more Attentions like Pure ads.
• There are some services to optimize the matching between a company and a job seeker but it's still a beginning phase.
• We can find the similar service to DMP to be the collection of user data but I don't think it works for Look-alike.
• Very weak Tracking players in the ecosystem of recruitment.

Predict the future of recruitment

Based on thinking of the history and the ecosystem of both internet ads and recruitment, personally, I'm thinking that these 3 movements will occur on the recruitment from now on.

• Service to promote Attention -> Interest in recruitment activities of companies.
• Service to optimize or automate the list up or suggestion or share of job seeker data with integration and segmentation.
• Quantitive analysis, A/B test.
• Service to optimize the matching between a company and a job seeker with quantitive data.

Suggestion on Jobright

Jobright is the web application for companies in SEA to manage, analyze and optimize recruitment process using AI. By providing a mechanism that makes it possible to reasonably judge "Just because" of human beings, we'd like to resolve the problem of mismatching of recruitment.

Through this service, we're planning to develop the features like DSP, DMP and tracking for automatic optimized matching and Look-alike.

This is still in the closed beta version now (2018/Apr) and we provide this application only to IT companies (functionally matches with only IT companies so far). If you are interested in this service, we can invite it so please contact us from the contact form.

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About Tomohide Kakeya

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