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The huge change coming to Dan Murphy's that could make your next beer shop VERY different

Dan Murphy s workers will be taught to recognise the signs of domestic violence as part of a training scheme being rolled out to more than 28,000 staff.
Staff at the liquor chain, BWS and Jimmy Brings will start training in 1,400 stores nationally this week to help them notice customers who are victims of family violence.
The training program was set up after a young woman sought refuge from her male partner inside a BWS store earlier this year.
Dan Murphy s workers will be taught to recognise if customers visiting their store are victims of domestic violence as part of a new training program (stock image) ....

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Global Automotive Leader Servco Increases Customer-Centricity with Amperity's CDP Integrating Data Across Their Enterprise To Power Marketing Solutions and Customer Insights

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SEATTLE, March 3, 2021 /PRNewswire/ Amperity, the #1 enterprise customer data platform for consumer brands, today announced Servco Pacific Inc. (Servco), a leader in automotive products & services, has deployed Amperity to connect silo d customer data across its businesses, create highly accurate 360-degree views of their customers and households, and get actionable business insights to better build customer trust.
With Amperity, Servco now brings teams together across its entire global portfolio leading to more personalized and effective business analytics and coordinated marketing campaigns.
Enabling brands to deliver on exceedingly high customer expectations has become even more important during the pandemic, said Brian Goldfarb, chief marketing officer at Amperity. Servco has unlocked a deeper, more actionable understanding of their customers with Amperity in record time, driving real bottom line results, and improved ....

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Woolworths, Westfield, Appen, Wisetech, Medibank: All the half-year results here

4.43PM â Feb 24, 2021
Harmoney, MoneyMe lift personal loan originations in bank tech battle
Loan originations are on the rise at two new, tech-driven personal lending brands, Harmoney and MoneyMe, which presented plans to beat the major banks at finding customers and assessing their risk but failed to convince the market.
Harmoney and MoneyMe have both developed machine learning tools using broad data sets to assess customers; Harmoney said a new model using data from 53,000 Australian loan applicants had resulted in its âLibraâ system doubling originations in the middle two weeks of February.
Over the half, Harmoneyâs $194 million of new loans was down 28 per cent, adding to the negative sentiment on the market. But it explained this was due to a COVID-induced pullback in the first quarter and said new loans were up 47 per cent in the second quarter and momentum is continuing. Itâs total loan book is $470 million including New Zealand, whe ....

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Woolworths HY Profit Up 28.0%; Sees Endeavour Separation To Take Place In June 2021

CANBERA (dpa-AFX) - Woolworths Group Limited (WOW.AX) reported that its net profit after tax attributable to equity holders of the parent entity after significant items for half-year period ended ....

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Amperity Receives 5th Patent for Identity Resolution Technology

Amperity Receives 5th Patent for Identity Resolution Technology
Latest Award Further Distinguishes Amperity as The Only CDP With Patented Innovations For Driving Customer Centricity
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SEATTLE, Feb. 24, 2021 /PRNewswire/
Amperity, the #1 enterprise customer data platform for consumer companies, today announced that it has been awarded
U.S. Patent 10,922,337 for Clustering of data records with hierarchical cluster IDs. This award is the
fifth patent granted for Amperity s core identity resolution and customer 360 technology, and further cements its platform as the only Enterprise CDP with protected innovations that help drive customer-centricity.
Customer data is a mess. Brands want to personalize each interaction with their customers, but often end up falling short of this ideal because the data doesn t cooperate. Many high quality personalized experiences require using more of this messy data, not less. But ....

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