What insights can be found in Social Media? [An inside look at LeadSift] - LeadSift - Steal Leads from Your Competitors
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What insights can be found in Social Media? [An inside look at LeadSift]

Posted on 21 May

When we explain that LeadSift helps brands reach in-market consumers through intent data, actionable insights and bigger audiences we are often compared to social listening platforms. Which is understandable since social listening platforms in general mine or capture data from social media sources. However, there is definitely a distinct difference between LeadSift, social listening platforms and native social media sources like Twitter. As we receive this certain set of questions quite often, we decided to provide an inside look at LeadSift.

How is LeadSift different from a social listening platform?

Although some people would liken us to a social listening platform or believe that a social listening platform provides the same functionality, LeadSift is very different from a Sysomos or a Radian6, for example. In fact, we believe where a social listening platform ends – LeadSift’s functionality starts.

A listening platform pulls in data based on keywords mentioned around your brand, competitors or industry. Each of those keyword mentions or posts has a real social user behind it. LeadSift analyzes posts through a semantic understanding of the message within the post, identifies those consumers expressing intent to purchase and captures them as in-market consumers.

For each individual in-market consumer, LeadSift generates a 360-degree view of their demographic, interest and behavior attributes allowing brands to understand “Who they are”, “How they behave” and “What they do” at an individual and aggregate level. With this level of insight brands and agencies can activate marketing campaigns and craft messaging and creative that will resonate at a very personal level.

But can’t social listening platforms do that?

Listening platforms are limited to the keywords added when a data collection approach is defined. Although Boolean logic and proximity can help capture some of these in-market consumers the user is tasked with the expansion of keywords and ultimately charged for results that may provide false positives.

Here is an example for identifying in-market car consumers:

Search keywords:  “Car” and “Shopping”

A LeadSift collected post: “Going car shopping this weekend- big decision ahead!”

A listening platform false positive: “Dad gave me the car- going shopping with the girls!”

In terms of the demographic, interest and behavior attributes extracted on consumers, LeadSift has built this functionality in-house to infer the data with great accuracy. It is essentially first party data on the user and a level of insight not available through a social listening platform.

Can’t I target that on Twitter anyways?

Twitter does allow for various targeting options natively through their ad targeting. However, you never have insight into the actual individual users you are targeting. Your ad will reach only the Twitter users that match their internal algorithms and will do this without you knowing who this ad will be shown to. With insight at the individual user, you know who they are as both as a social consumer, as well as a collective audience.

These insights can also be used for more personalized targeting through additional insight filters via the Twitter Tailored Audiences approach (Minimum of 500 users targeted) or leveraged to better target groups through matching against the native targeting on Twitter for its other ad products.

Are these insights from LeadSift specific to Twitter only?

Although LeadSift insights are extracted from Twitter they are valuable to leverage outside of Twitter and even outside of social because they are actually insights on a digital consumer’s demographic, interest and behavior attributes. This means they can be used to provide insight for targeting on Facebook Custom Audiences and for cross-channel ad buys – websites your audiences are frequenting for banner ad placement, what TV shows they are watching for broadcast advertising or sponsorships, and on the blogs/ forums with active and engaging communities. The data from LeadSift can also provide high-level insights to ad networks, allowing for better placement on other digital properties.

Can you always find enough in-market consumers?

LeadSift’s algorithms will capture only conversations expressing intent – which are very prevalent for many B2C brands. We have strived to ensure our in-market consumer identification provides the best means possible to capture consumers in the moment. Through understanding of the demographic, interest and behavior attributes of these in-market consumers we are able to produce look-alike audiences from over 175 million social consumers indexed to scale audience segmentation for digital marketers.

Does this work for both B2B and B2C?

LeadSift is being used for both B2B and B2C customers.  Although there are many more in-market conversations around B2C brands there is a great deal of conversation around B2B in-market consumers that will allow your brand to activate campaigns around these users as well.

How accurate is your data?

LeadSift accuracy is dependent on the individual insight that we capture on the user. We have developed training sets of data for every insight we provide allowing for accuracy between 80-95%. Although there will be inaccuracies and false positives with every data set we strive to continuously optimize our accuracy through advanced data techniques.

Do you offer Twitter only?

LeadSift’s initial focus was on Twitter data but we have recently added Instagram as a data source and are exploring numerous other social data sources for proper data extraction to be used for digital marketing activations.

How does Twitter compare to Facebook?

LeadSift considered Twitter users for extracting insight because we believe there is great leverage over to the digital user. While it can be assured that every Twitter user is on Facebook the opposite is definitely not the case. Understanding the digital consumer on Twitter allows for proper extrapolation onto Facebook and digital users as a whole. Also since Facebook’s data is protected by privacy, complete insight into these users as individuals is limited.

Do you have a question about LeadSift that we might’ve missed?

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