{"id":117590,"date":"2015-10-15T14:40:00","date_gmt":"2015-10-15T19:40:00","guid":{"rendered":"https:\/\/www.dacgroup.com\/getting-good-data-an-excellent-example-from-the-economist-2\/"},"modified":"2025-12-17T09:43:21","modified_gmt":"2025-12-17T14:43:21","slug":"getting-good-data-an-excellent-example-from-the-economist-2","status":"publish","type":"post","link":"https:\/\/www.dacgroup.com\/en-ca\/insights\/blog\/analytics\/getting-good-data-an-excellent-example-from-the-economist-2\/","title":{"rendered":"Getting good data \u2013 An excellent example from The Economist"},"content":{"rendered":"

We love data. It helps inform everything we do, backs up everything we say, and helps demonstrate our success. But often the challenge is how to gather that data in the first place. Analytics is a great start, but what if you need more qualitative data?<\/p>\n

Most of the data we can collect with web tracking is quantitative: bounce rates, conversion rates, shopping funnels, etc. All of these numbers are created by analysts for analysts, but they make normal marketers confused and uncomfortable. They want to focus on quality and experience \u2013 the human factors \u2013 not numbers and statistics. So they end up relying on their gut-feeling. In comparison, qualitative marketing research are seen as the bearers of human attitudes and opinions.<\/p>\n

But what if we merge qualitative and quantitative data about the same customer? What can statistics and human attitudes tell the company about the perception of their brand, special offers, trust to marketing channels, product preferences, loyalty?<\/p>\n

That is exactly what The Economist set out to do with their latest online survey aimed at collecting the qualitative data about their customers’ behaviour. By merging this data with on-site behavioural analytics, they can predict the likelihood of different potential customers buying different products.<\/p>\n

When I saw a pop-up offer on Economist website to take a part in their qualitative survey, I started answering questions purely out of curiosity. I went through 20 or 30 questions just answering the questions like normal people would do. But then I reminded myself that I am an analyst, so I went back through the whole survey again to better understand marketing and data intentions behind the survey questions.<\/p>\n

Here are a few observations I would like to share with you.<\/p>\n

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  1. \u00a0Survey pop-up.<\/strong><\/li>\n<\/ol>\n

    There is no strong motivation to complete the survey yet which makes me wonder how many people click on that red button. \"Economist_Take<\/a><\/p>\n

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    1. Prize as an incentive for participants to complete the survey. <\/strong><\/li>\n<\/ol>\n

      It\u2019s only after<\/em> you click through that you are told about the prize draw. In my opinion, this should be on the front page, serving as a strong incentive for click throughs.\"Economist_Motivation<\/a><\/p>\n

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      1. High-level customer segmentation based on the perceived likelihood to buy<\/strong><\/li>\n<\/ol>\n

        The first question segments responses based on their likelihood to buy with the current packages and offering. This will help them understand where there is an opportunity to upsell and what might create new subscribers, as well as assessing the value of individual responses in developing new products and packages.<\/p>\n

        For example, if a respondent said that they have never and would never consider subscribing to the Economist, their responses will be less useful in devising new subscriptions packages \u2013 they\u2019re not going to subscribe anyway!\"Economist_Likelyhood-to-buy<\/a><\/p>\n

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        1. Investigating product preferences<\/strong><\/li>\n<\/ol>\n

          The value of print publishing is declining \u2013 the costs are high and the readership steadily declining. Yet some people still much prefer print, deriving value from the tangible. With this question, The Economist can spot trends in publishing, helping them to assess the value in continuing their print magazine.\"Economist_Product<\/a>\n

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