Feeding Your Dashboard with Quality Information

We collect the data you need to grow your brand so you don't have to. Our data collection process is not a secret - let us tell you how we do it.
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Where We Get Our Data

Latana sits under the Dalia Research umbrella. Dalia is a powerful survey engine for real-time market and opinion research. What is amazing about Dalia is that its platform can be integrated into anything from freemium apps to web advertisements and custom target approaches. As a result of these integrations, Dalia has instant access to 40,000 apps and websites. Still with us, good?

Dalia leverages these apps and websites to be able to distribute 5 million micro-surveys per month to people living in over 100 countries.

It lends its technology to us so that we can deliver the essential insights your brand needs to thrive. You are in good hands. Stanford University, Millward Brown, and The Guardian newspaper all use Dalia’s data too.

Gathering survey respondents isn’t enough. We take a step further to ensure you receive only quality data. We do this by dynamically profiling each potential respondent across key demographic, psychographic, and behavioural attributes. Then, using machine-learning algorithms that analyse active and passive data, we generate a quality and trust score for each potential respondent.

An audience attribution engine matches qualified respondents to a survey targeting their profile. Sounds pretty tech heavy, and it is, but it guarantees that only engaged and accomplished people complete each survey.

Image depicting survey respondents

Where We Control For Real World Changes

We don’t do random. We do precise and accurate. Therefore, any changes you might see are based on real world changes because we take the time to control our sample for a large number of variables. We’ve invited a few friends to show how controlling works. In traditional quota sampling, usually just age and gender are controlled to maintain sample composition.

Let’s take this as an example:

A survey of 1,000 people with the following distribution, in terms of demographics.

500 Male / 500 Female

Image depicting controlling real world changes

Age and gender are controlled so the researcher will make sure that the ratio of both is maintained in the next survey.

This is to ensure the results are comparable. Bear in mind that only these variables will be controlled. Let’s keep this information in mind and move onto the next survey.

Here, the sample composition dramatically shifts towards urban location:

500 Male / 500 Female (stable, because controlled)

600 young / 400 old (stable, because controlled)

800 urban / 200 rural (skewed, because not controlled for)

variable controlling

The demographic groups in the first survey are fundamentally different from each other. Because of this, it is now likely that you will see changes in the results because of the higher proportion of the urban population in the sample.

This is important because, particularly when it comes to brand perception, such demographic variables can have a great impact on brand performance.

So, what does it mean for you when you receive insights from surveys where the minimum variables have been controlled? Misinformation.

The insights are not based on real-world changes but rather changes in sample composition. Basing decisions on inaccurate insights can be dangerous for your brand.

Cartoon depiction of insights

Only Accurate Data with Latana Brand Analytics

We go above and beyond our competitors to make sure that the data we provide is trustworthy and actionable. We want you to be confident your brand is moving in the right direction, be able to base future decisions on our insights, and track brand performance across your target audience. And you can with brand analytics.

Image depicting accurate data