UK retail brands are set to embark on a groundbreaking journey towards more ethical and inclusive marketing, driven by a greater understanding of national consumer behaviour. Predyktable, a trailblazing advanced data analytics company, combines rich data, advanced AI, and data science to equip retail marketers with predictive insights. This will enable them to meet evolving community needs in challenging markets and create more ethically and inclusively focused services products and experiences for a diverse range of customers.
Predyktable’s innovative approach is reshaping the retail industry’s response to dynamic customer behaviour, promoting diversity and inclusion through four key strategies:
- Inclusive targeting: by deeply understanding wider community needs and behaviours, retail marketers deliver products and services that are resonant to underserved or marginalised communities.
- Eliminating bias: machine learning algorithms remove bias from prediction data, so when retail brands make marketing and product recommendations, they avoid reinforcing stereotypes and discriminatory practices.
- Tailoring recommendations: marketers meet the unique inclusivity needs of different communities using predictive recommendations to customise products or services with accessibility features, cultural considerations and more.
- Predicting demand: equipped with predictive insights on dynamic demand, marketers deliver the right products and services, to the right place, at the right time: and better serve underrepresented and vulnerable communities.
The industry-first catalyst is Predyktable’s ‘dynamic consumer behaviour engine’ that processes thousands of economic, environmental, demographic, social data sources, and its own extensively researched datasets including region-specific events.
These diverse data signals are combined with retail brands’ own historical data. Machine learning reveals complex, cause-and-effect, behavioural patterns, and relationships within the data. These feed bespoke, real-time, predictive insights and recommendations that augment forward marketing decisions.
As fresh data is added to the consumer behaviour engine, including the collective learning of anonymised client data sets, existing models are continually retrained with this data. Keeping the models current with shifting trends, behaviours, and sentiments is critical to consistently delivering highly accurate, timely predictions that stay in tune with customers’ needs.
Predyktable’s pioneering innovations address the factors that constrain more ethical and inclusive future decision-making. These issues are highlighted in Predyktable’s 2023 UK survey which questioned over 100 retail marketers.
Over 65% of respondents revealed their current data analytics tools lacked value and were not tailored to their forward-thinking needs. Furthermore, 50% cited the use of poor-quality data, while a lack of focus on external data sources hindered the depth and quality of insights.
The survey also showed that while 70% of marketers consider predictive data analytics pivotal to success, a staggering 86% were not currently using such tools to augment their decision-making processes.
Phillip Sewell, Predyktable’s CEO and co-founder said: “It’s clear that retail marketers urgently require smarter ways of better understanding and predicting how diverse consumer behaviours impact on what when and how people shop. However, for predictive analytics to really deliver, marketers need higher quality data, enriched with much wider external sources. This feeds more accurate predictive insights that removes guesswork, bias and uncertainty. It leads to more ethical and inclusive marketing practices generating optimal returns that benefit everybody.”
