{"id":5417,"date":"2014-12-16T16:30:03","date_gmt":"2014-12-16T16:30:03","guid":{"rendered":"https:\/\/www.gosquared.com\/blog\/?p=5417"},"modified":"2019-11-28T11:59:18","modified_gmt":"2019-11-28T11:59:18","slug":"converting-seasonal-shoppers","status":"publish","type":"post","link":"https:\/\/www.gosquared.com\/blog\/converting-seasonal-shoppers","title":{"rendered":"Gaining loyalty: 3 tips for converting seasonal shoppers into long-term customers"},"content":{"rendered":"

Christmas and nearly every other holiday event brings large traffic spikes to ecommerce stores.<\/p>\n

The problem, however, is even when your visitors convert into sales, those customers rarely return. If they do return, it’s often not until the next seasonal deal or for another promotion.<\/p>\n

Is the seasonal rush a good time to start building relationships? Who even are these seasonal shoppers? Most importantly, how does high sales activity in December translate into loyal customer activity later in the year?<\/p>\n

Audience analysis: the surgical shopper<\/h2>\n

Over the past few years, consumer behaviour changed quite dramatically. An ideal customer for an ecommerce store might go through the buying process like this:<\/p>\n

\"Ideal<\/p>\n

The profile we\u2019ll be focusing on is the surgical shopper<\/b>. They have probably done extensive research on what they want and they go through ecommerce stores very efficiently.<\/p>\n

Despite a lot of talk about the surgical shopper, how do we know exactly what they look like? We need a quantitative definition and that’s where we’re going to start.<\/p>\n

Construct the surgical shopper\u2019s profile (and bring data!)<\/h2>\n

First thing\u2019s first: if you\u2019re not tracking anything on your site, you won\u2019t get very far.<\/strong> Everything that can be tracked, should be tracked – the only thing that changes is your focus on what metrics to analyse. Let’s visualise the differences between different shopper profiles:<\/p>\n

\"Data<\/p>\n

Let\u2019s look at some examples of classic surgical shopper behaviour and how we can spot those attributes with data:<\/p>\n