How LinkedIn continuously improves their products by making use of Smart Tech

Interview

When thinking of smart technology, most of the people would refer to technology that is able to analyze data, interpret this data and finally determine the best next logical steps. Just the same as what human beings would do. The source of the data is not considered important for ‘Smart Tech’. The data could be readily available or being provided by sensors. To find out what Smart Tech means for Steven and Charu, Compact asked them to give their definition.

Steven: Smart Tech is a loaded term. I initially thought of Internet connected light bulbs, Artificial Intelligence (AI) and Amazon Echo. For me the technology has to have deep intelligence and use some amazing new technologies. What is the problem that is being solved, and is this a basic human need? Is it really going to make people’s lives better?

An example: I received an email from Amazon that they had refunded my order. I thought to myself: “I did not request a refund”. I continued reading the email, and it said that Amazon noticed that the movie I rented and played on my computer was streamed down, and that the average bit rate was sub-optimal. Very smart, very pro-active. They have a clear optimization option of lifetime value. They understand all the inputs, and they are really smart to make sure that I am having the best experience possible with their products and services.

Charu: What is interesting about this example is that it is not something that was explicitly asked for. Amazon is anticipatory, and they just delighted Steven: “Wow, I didn’t even know that they would do something like that”. Services that strive to anticipate these unvoiced needs not only create a better experience for their users, but drive brand loyalty and adoption for their product.

Steven: Another example is Google Maps. It is amazing that when you land in a new country, it knows where you are, because it uses the location on your device. Based on this it tells you how to say “hello” and “thank you” in the local language, what the currency and the exchange rates are, and what the weather is nearby. That is a total game changer.

For me, Smart Tech is what you can do on a device, the amount of data that is available about you and making this very personal, very targeted and very smart about anticipating the next thing that you want to do.

Smart Technologies

Both LinkedIn.com and Sales Navigator (or part of their product features) could be regarded as smart technologies as well. First of all there is a focus on data gathering and continuously improving the quality of the data (e.g. information about members, jobs, companies, connections, skills, learning content). For professionals it is easy to join as a member, which is free of charge, and connect to other members. At the moment of writing this article there were more than 560 million members globally, and this number is growing. What makes LinkedIn different from other social networks like Facebook is the business model behind it. LinkedIn’s business model is based on several key offerings: Talent Solutions for recruiters, Learning Solutions for talent development, Marketing Solutions for marketers, Sales Solutions for sales professionals, and their premium subscription product.

Having all this data helps the products to be regarded as Smart Tech. With algorithms LinkedIn and Sales Navigator could provide better insights to the users, and also help them to perform their activities better. Some examples of this are given below.

Charu: If you are filling out your profile, one of the biggest challenges is the summary section; so we created an auto-generated summary feature. We use all the other information on your profile and machine learning to propose a summary based upon everything else that you have entered.

Another feature is Resume Assistant. Resume Assistant in Word retrieves information from your LinkedIn profile, and helps to write your own creative CV, by showing you examples of how real professionals in the fields you are interested in describe their work experience and skills. These details serve as inspiration for people to help write their personalized CV. It is machine learning that correlates skills that we have found according to job titles of people in the same field across LinkedIn profiles and lists common skills.

Acquisitions

Both LinkedIn.com and Sales Navigator have product visions that serve as a roadmap for their future development. Key stakeholders (all the way up to the C-suite) are involved to set a strategic focus on what is really important on these product visions. Development items are based on customer needs, and the continuous focus on how to provide the insights and pieces of information that help members and customers to do something more effectively. At the same time it is important to maintain the human touch with it.

Product features are mainly developed in-house, and by running experiments the final shape of the feature is defined. Not all developments are done by the LinkedIn product teams themselves. Sometimes other (new) Smart Tech solutions, which are related to features in the product visions, are identified in the market. In that case it could be more interesting for LinkedIn or Sales Navigator to acquire and integrate these Smart Tech’s into these products, instead of developing the features in-house.

Charu: We are lucky to have incredibly talented machine learning scientists and a data scientist team behind all of what we are doing. We have the luxury of being able to build a lot of the Smart Technology in-house.

There have also been some acquisitions, like Pulse in 2013: a popular app that aggregated the latest trending news. They had strong engineering teams that built great algorithms, and helped to kick start the news feed part of the platform.

Steven: From a Sales Navigator perspective we have also made a number of acquisitions over the years. One of the acquired companies was called Newsle, which gave people relevant news and info about their most important contacts. We also acquired a company a few years ago called Fliptop, that powered the back-end technology that provides our CRM synchronization infrastructure. Last year we bought a company called PointDrive, which allows you to send beautifully organized sales collateral to your prospects. We have made these acquisitions because there is a product vision that we want to achieve, and the acquisitions help us get there. And most recently, we purchased Heighten, which will power our upcoming deals feature; making pipeline management much smarter for managers and sales representatives in all of these examples.

The future

When looking at LinkedIn and Sales Navigator, the Compact team is interested in what the vision of Steven and Charu is towards the future.

Steven: We want to be in all the apps that sales people are working with. This gives us the opportunity not just to save them time, it also provides a common identity and set of insights that we can directly deliver to sales people.

Furthermore, we want to answer the question: ‘what is the next best action?’. If you want to setup an automated email cadence today, it is based on: ‘did I send the email?’, ‘did it get opened?’, ‘when did it get opened?’, ‘maybe we can do some things from there?’. That is not very intelligent.

It does not take into account whether the recipient actually engaged with that content, how new they were in that job, what company they work for and who are the other people that opened it.

We are uniquely positioned to go after that type of vision. We really do have that professional identity of record, and we can make this more human and more relationship-based.

Charu: I think that LinkedIn can play a really strong role in big technology shifts that are happening in industries, because we have so many insights. For example, trends around ‘what is happening in your city?’ and ‘what is happening in the companies in your city?’. We always think about how we can be smart, and provide you with the right information at the right time, so that you do not get caught up as collateral damage at times when these big shifts happen. Large technology shifts do not take everyone along with them, and it is important for people to understand what skills they may need to learn, or other industries and roles they need to consider.

For example, seven years ago when mobile development really started kicking off, many companies started switching. Consumer companies focused their efforts on mobile products and apps. LinkedIn was one of the first places where you could see the trends of all these mobile technologies and companies in our data. You could literally visualize it as it increased.

Final note from the author

On 25 May 2018, a couple of weeks after the interview, the General Data Privacy Regulation (GDPR) became active within Europe. In order to comply with this regulation, LinkedIn updated their products, privacy agreements and customer agreements. Users in Europe now have more control over how and which personal data is being captured and tracked, and how this can be deleted and corrected.

What the impact will be on the effectiveness of LinkedIn’s Smart Tech solutions is not yet known, however it is to be expected that there will be some implications, as user data may only be used for the clearly defined purposes, which users have to agree with upfront. Especially in the area of recruiting and marketing this will be interesting: what is still allowed for LinkedIn’s customers (like recruitment agencies), and what is not? Sending general advertisements without explicit user consent is not permitted, however is it still acceptable to connect to users on a social network? Only time will tell…