Power through peaks with purpose driven personalization - New York

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The five hottest tips for fashion brands and retailers on how they can adopt personalization.

Last week Qubit hosted an event at Soho House, New York, to celebrate our latest research, ‘Personalization in Fashion’. The event welcomed fashion and retail leaders to join us for the morning where we teamed up with Lilly Pulitzer, Google Cloud and Mobify.

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Topics for discussion

The morning was broken down into three sections as we welcomed different speakers to the stage. To kick things off, we had Carly Pietrobono, Retail Strategist at Qubit who highlighted key personalization tactics to help supercharge efforts, particularly in the lead up to Black Friday.

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Up next, we had Alex Olivier (AO), Qubit’s Technical Product Manager, who showcased the traffic some brands handle during peak times. AO highlighted an example of when an influencer or celebrity endorsement is shared on social media, or during the busiest hours on Black Friday. He also covered the key trends from last year’s Black Friday period - this demonstrated how to handle real-time reporting for added visibility during such intense times.

Additionally, Lilly Pulitzer, who is a fantastic example of a brand that puts mobile at the very heart of the customer experience, showcased results that prove by focusing on delivering a better customer experience, they were able to boost mobile revenue by 49%. This was driven by 36% more transactions and 10% higher average order values.

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For those of you who were unable to attend the event, we’ve rounded up the highlights for you.

The five hottest tips and statistics

1. Personalization starts with data and you should be looking at three sources:


  • Behavioural data, this is collected from your site. It’s specific to personalization and captured through your data layer.
  • Quality data is from asking your customers, this is typically in a survey format. It links to psychographic and intent data where you’re asking your customers in order to understand their values, beliefs, opinions and attitudes.
  • Data from key business areas. Back-end data that can be imported from a variety of different sources. Transactional data from your store, demographic, CRM, Loyalty and a lot more.

Then the challenge is just aggregating the data from all three of these sources and accepting it in a meaningful way.

2. Segmentation and product recommendations are a great place to begin on your path to personalization. Both are fairly standard in a strategy, but are rarely used to full effect.

3. 81% customers are open to switching loyalty to sites that provide a better, more personalized experience.

“Brand loyalty is at an all time low and is essentially up for grabs. Consumers have grown tired of the facade that’s typically portrayed on social media and are looking for really individualised experiences” said, Carly Pietrobono, Retail Strategist at Qubit.

4. A lot of the businesses we work have began to focus much more around lifetime value, loyalty and retention. Ultimately, this is where you can truly get those valuable customers. “The saying, ‘20% of our customers make up 80% of revenue’ really does apply, and especially around these kind of peak periods.” Said, Alex Olivier, Technical Product Manager.

5. There has been a shift in customer behavior during the Black Friday shopping period. We have particularly seen a change from returning visitors, this opens a key opportunity to re-engage with these customers, serving them the right message based on what you already know about them.

Qubit's data from our retail customers shows that 27% of customers who shop during the Black Friday period, here's some of the repeat purchase trends seen from our retail customers:

- 17% purchase again before the end of Cyber Monday
- 60% purchase again before Christmas Day
74% purchase again by end of Jan sales

To discover more on how you can use personalization to satisfy your customers and increase your top line revenue; download our brand new report ' Personalization in Fashion'.

Personalization in Fashion - cta

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