CDP for retail
Customer data marketing for retailers
Get better, faster data and built-in analysis to turn shopper interactions into sales.
Your retail customer data challenges
Because there’s so much customer data in retail, the opportunities to turn that data into marketing that generates sales are bountiful.
But time and time again, retail proves to be one of the hardest spaces to effectively use customer data to create truly genius marketing. That’s because…
- You have to deal with messy, incomplete or outdated data (duplicate records, missing values, etc.) that can mislead marketing decisions.
- You’re hunting data across multiple silos from in-store to online sources (CRMs, POS systems, e-commerce platforms, etc.), meaning you never get a 360-degree view of your customers.
- You have to adapt to customer behaviours that can turn on a dime, so the data you collect today might not reflect their needs tomorrow.
- Your vast amounts of data are useless if you can’t drive actionable insights from it and activate it.
How predictive analytics in retail can help
Our technology platform, Unilyze, turns customer data into real competitive advantage for some of the world’s most data-savvy retail brands — so customers keep coming back for more. Find out how predictive analytics in the retail industry can help, whether it’s for banking or online and physical stores.
Connect, analyse and activate in-store and online retail data easily
Our solutions cater to retail customer data marketers by offering:
- Continuous data integration from vast numbers of customer interactions
- Advanced matching with a real-time database
- AI-powered smart audiences that help you forecast, target and predict the behaviour of your customers
- Customer experiences based on past, present and predicted behaviours
Respond to specific customer needs as soon as they happen
You can personalise experiences, based on hyper-relevant data exactly when (and where) it matters most, with
- Real-time website personalisation based on in-moment behaviour
- Advanced product and category recommendations based on a customer’s projected propensity, such as browse abandonment suggestions
- AI-generated, personalised content that’s designed to increase engagement
Continuously improve campaign performance
Discover an intuitive interface and customer dashboards that eliminate the need for SQL expertise, allowing you to:
- Utilise A/B testing on customer data to drive targeted marketing strategies and improve conversion rates
- Explore business hypotheses suggestionsOptimise audiences in real-time based on your brand’s specific contact rules
- Drive insight and develop practical segmentations
Retail CDP case studies
Don’t just take our word for it — read up on our retail case studies to learn more about how companies like yours use Plinc’s data solutions to elevate and activate their customer data.
Crew Clothing get real-time insights in their Black Friday war room
Q. How did Crew Clothing get customer insights in their Black Friday War …
Halfords connects customer data to promote loyalty
Q. How did Halfords deliver real value through their loyalty program?…
M&S International use Future Value Model for promotional segmentation
To increase retention and optimise marketing spend across these markets, …
Matching diners to dinners at Prezzo
Q. How did Prezzo streamline its voucher promotions process and accurately …
SCV powers customer-centricity at Halfords
Q. How can Halfords understand customer behaviour groupwide to develop a …
Hyper-personalisation boosts PlayStation’s engagement by 30%
Q. How did PlayStation achieve a massive 30% increase in engagement across …
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