Author: Phillip Sewell

Navigating Hospitality’s Choppy Waters: How Predictive Demand Forecasting Can Steer You Towards Success

Posted on by Phillip Sewell

As the CEO of a predictive analytics company, I have seen first-hand the immense pressure facing the hospitality sector. Staff shortages, rising costs, and the ever-growing need for sustainability are creating a perfect storm that threatens to capsize even the most established businesses.

In this blog we explore how predictive demand forecasting can help businesses effectively navigate these challenges.

navigate predictive demand forecasting with Predyktable

The big “4” challenges and the solutions 

1. Staff Shortages and Retention: 

A staggering 92% of UK hospitality businesses reported staff shortages in Q4 2023, with the situation expected to worsen. (Source: [https://wsta.co.uk/facts-figures/])

Solution: Predictive analytics can help forecast staffing needs based on anticipated occupancy. This allows businesses to schedule more efficiently, avoiding overstaffing during quiet periods and understaffing during peak times. This not only reduces labor costs but also improves employee morale and the overall guest experience.

2. Cost of Living Crisis: 

Inflation in the UK hit a 40-year high of 10.5% in December 2023, putting immense pressure on already tight profit margins. (Source: [https://www.ons.gov.uk/economy/inflationandpriceindices/bulletins/consumerpriceinflation/previousReleases])

Solution: Predictive analytics can help businesses optimise their pricing strategies by taking real-time demand and competitor pricing into account. This allows them to maximise revenue without deterring customers by setting prices that reflect market conditions.

3. Increased Running and Ingredient Costs: 

From rising energy bills to higher food prices, businesses are facing significant increases in running and ingredient costs. (Source: [https://www.businessgrowthhub.com/blogs/2024/01/challenges-and-opportunities-for-the-hospitality-sector-in-2024])

Solution: Predictive analytics and predictive demand forecasting can help businesses optimise inventory management by forecasting demand for specific items. This helps in reducing waste and allows businesses to purchase only what they need, leading to lower overall costs.

4. Environmental Considerations: 

Consumers are increasingly demanding sustainable practices from businesses, with 78% of UK consumers willing to pay more for sustainable travel and accommodation options. (Source: [https://www.ukhospitality.org.uk/2146-2/])

Solution: Predictive analytics can help businesses optimise energy consumption by forecasting occupancy and room usage. This allows them to implement energy-saving measures more effectively, such as adjusting heating and cooling based on real-time needs. This not only benefits the environment but also helps to reduce energy costs.

predictive analytics and predictive demand forecasting with predyktable

Conclusion

In conclusion, the UK hospitality sector is facing a complex landscape in 2024. However, by embracing predictive demand forecasting, businesses can gain valuable insights and make data-driven decisions to navigate these challenges and emerge stronger. 

By optimising staffing, pricing, inventory management, and energy consumption, businesses can not only lower operating costs and improve efficiency but also enhance their sustainability and attract environmentally conscious consumers. 

Predictive analytics is a powerful tool that can help the hospitality sector weather the storm and chart a course towards success in today’s dynamic market.

Investing in the Future:

Implementing a predictive analytics solution (predictive demand forecasting) might seem like an additional expense at a time when cost reduction is crucial. However, consider it an investment in the future of your business. This technology can be the difference between struggling to survive and thriving in a competitive and ever-changing landscape.

At Predyktable we understand the unique challenges faced by the hospitality industry, and we are committed to providing solutions that are affordable, easy to implement, and impactful. We offer a variety of flexible options to cater to different business needs and budgets.

Demand Forecasting: why external data get’s you closer to the truth

Posted on by Phillip Sewell

In today’s lively and interconnected business landscape, the traditional approach to demand forecasting, relying solely on internal data sources like sales history and inventory levels, may fall short of delivering the precision and adaptability needed to stay competitive. To address this, forward-thinking businesses are recognising the immense value of incorporating external data sources into their demand forecasting strategies. These external data sources open up a wealth of insights, empowering companies to make more informed decisions in the realms of inventory management, staff planning, and marketing campaigns.

The advantages of leveraging external data sources in demand forecasting are manifold, but let’s delve deeper into the rationale and benefits of this strategic shift.

Demand Forecasting

Comprehensive Understanding of Demand Drivers: 

External data broadens the horizon of knowledge, providing a holistic view of the forces shaping demand. This comprehensive understanding of demand drivers not only empowers businesses to make more informed decisions, but also positions them to navigate the complexities of today’s interconnected and rapidly changing world with greater agility and precision. Some key areas to capture data are; 

  • Economic Indicators: External data sources, such as GDP growth, unemployment rates, and consumer confidence, provide a macro-economic perspective. These indicators can signal shifts in consumer spending patterns and provide a nuanced view of market dynamics. For example, an uptick in GDP growth might indicate increased consumer confidence, signalling potential growth in demand for certain products or services. 
  • Industry Trends: Keeping an eye on industry trends, competitor activities, and regulatory changes is crucial for staying ahead of the curve. External data sources offer valuable insights into market conditions, new product launches, and evolving customer preferences. This knowledge helps businesses anticipate demand fluctuations and seize opportunities that internal data alone often overlooks.
  • Social Trends: The digital age is providing us with a goldmine of information. External data sources encompassing product reviews, brand mentions, and customer sentiment can be harnessed to monitor consumer sentiment and track emerging trends. This real-time data enables businesses to respond swiftly to shifts in customer preferences.
  • Environmental Factors: Weather patterns and other environmental variables can significantly impact demand for certain products. For instance, data on temperature and precipitation can help retailers predict demand for seasonal clothing and adjust inventory accordingly.
  • Holidays and Special Events: External data sources often include holiday calendars and event schedules (e.g. gigs and sports), which can be crucial for demand forecasting. 
External Event impact on Demand Forecasting

By considering these external factors, businesses can elevate their strategic planning across various critical facets of operations, notably in the domains of marketing, promotions, and inventory management.

1- Marketing Campaigns:

  1. Precision Targeting: External data sources, such as holiday calendars and special event schedules, offer a roadmap for businesses to plan their marketing campaigns with precision. By aligning promotions with holidays and special occasions, companies can tap into the heightened consumer interest and capitalise on the increased spending that typically accompanies these events.
  2. Real-time Adaptation: Leveraging external data, allows businesses to adapt their marketing campaigns in real time. Monitoring things such as customer sentiment, national mood, and emerging trends, enables rapid adjustments to messaging and content, ensuring campaigns remain relevant and engaging.
  3. Timing and Messaging: Weather patterns and environmental data can influence not only the timing but also the messaging of marketing campaigns. For instance, if a sudden cold spell is expected, a clothing retailer can craft campaigns around the concept of “stay warm” to boost sales of winter apparel.

2- Promotions:

  1. Optimised Promotional Timings: External data sources, including economic indicators, help in pinpointing the optimal times for promotions. During periods of economic prosperity, customers may be more receptive to premium products, making it an opportune time for high-value promotions. Conversely, during economic downturns, value-driven promotions might resonate better with cost-conscious consumers.
  2. Competitor Monitoring: Industry trends and competitor activities can be invaluable for devising competitive promotions. By keeping an eye on what competitors are doing, businesses can craft promotions that offer a compelling edge in the market.

3- Inventory Management Strategies:

  1. Agile Stocking: Weather data is an asset for businesses with seasonal products. It allows them to anticipate fluctuations in demand and stock inventory accordingly. For instance, a ski equipment retailer can prepare for higher demand during the winter season and reduce inventory during the summer months.
  2. Demand-Driven Inventory: By incorporating external data sources into their demand forecasting models, businesses can synchronise inventory levels with projected demand. This not only reduces the risk of overstocking or stock-outs but also optimises working capital by ensuring that capital is not tied up unnecessarily in excess inventory.

In essence, by thoughtfully integrating external data factors into their planning processes, businesses can be more strategic and proactive in their approach to marketing, promotions, and inventory management. This, in turn, enhances their ability to respond to shifts in consumer behavior and market conditions, ultimately leading to improved operational efficiency, cost reduction, and greater profitability. It is a testament to the growing need for businesses to embrace the holistic insights offered by external data sources in navigating the complexities of today’s marketplace.

External data sources in demand forecasting

Benefits of Enhancing Demand Forecasting with External Data:

  • Improved Accuracy: External data sources supplement internal data by providing a broader context for demand forecasting. For example, by integrating economic indicators, businesses can better anticipate changes in consumer behavior. Similarly, monitoring social trends can reveal emerging patterns that might be invisible within internal data. The result is more precise forecasts, reducing the margin of error.
  • Reduced Risk: Businesses often grapple with the challenge of stockout or overstocking. External data sources act as an early warning system, signalling changes in demand patterns. For instance, by incorporating weather data, companies can predict demand variations for seasonal products, thereby mitigating the risk of stockout or excessive inventory holding. Economic indicators can help foresee shifts in discretionary product demand, allowing for more agile inventory management.
  • Better Decision-Making: The integration of external data sources provides a foundation for sound decision-making across various facets of business operations. For instance, demand forecasts can optimise inventory levels, ensuring products are available where and when customers need them. Additionally, these forecasts can guide production planning, aligning business capacity with anticipated demand.

In Conclusion:

The strategic integration of external data sources into demand forecasting represents a transformative imperative for businesses navigating the dynamic landscapes of today’s markets. This paradigm shift offers a comprehensive range of benefits, including enhanced forecast accuracy, operational risk reduction, data-informed decision-making, improved operational efficiency, cost reduction and increased profitability. The ability to swiftly adapt to market changes further solidifies the case for harnessing external data sources, ensuring that businesses not only survive but thrive in an environment where agility, precision, and data-driven insights are the hallmarks of success. It is a testament to the evolving role of data in shaping the future of business, driving resilience, competitiveness, and sustainable growth.

Advanced Data Analytics Partnership to Enhance Decision-Making in Retail and Hospitality

Posted on by Phillip Sewell

ClicData and Predyktable have joined forces to revolutionise decision-making in the Retail and Hospitality sectors. They are both at the forefront of helping businesses to make correct business-critical decisions in the face of constantly changing, complex environmental, economic, and consumer behaviours. This industry-first partnership introduces a comprehensive data analytics solution that empowers customers to not only manage their entire data lifecycle, but to act swiftly on accurate prediction insights powered by Predyktable’s predictive models. This collaboration opens up profit-generating use cases for UK Retail and Hospitality brands including optimising spend, demand forecasting, marketing strategies, labour allocation, and more, all based on increasingly precise predictive insights.

ClicData and Predyktable Partnership

Their approach transforms data analytics from hindsight into foresight, offering insights not just into what and why something happened, but also what might happen in the future and what to do about it. The UK’s expanding data reservoir presents an opportunity to harness data for predictive modelling. Real-time insights are essential for agile decision-making, and there is a growing need to bridge the skill gap in data and digital realms. This partnership offers a one-stop solution.

Predyktable leverages advanced AI and predictive analytics to provide a deep understanding of how consumer behaviour influences purchasing decisions. By aggregating a wide range of data, from global economic and environmental factors to regional indicators and industry-specific signals, their pre-built, Consumer-Behaviour Engine quickly builds accurate prediction outputs for organisations. Previously elusive, connected, patterns are revealed to generate foresight that fuels increasingly accurate recommendations on future actions. These results are automatically delivered back into ClicData’s platform.

“Our data platform excels at collecting, transforming, analysing, visualising and sharing any data: it’s powerful, smart and easy to use. We can now add further capabilities with Predyktable’s predictive analytics, so customers not only have a holistic and unified view of their organisation’s data, they now gain meaningful insight to accurately predict where their future actions will generate the greatest value.”- ClicData.

Phillip Sewell, Predyktable’s CEO and Co-Founder said: “This exciting partnership is about augmenting ClicData’s impressive data lifecycle management and analytics capabilities with predictive analytics. It’s the missing piece of the puzzle that drives more informed, contextual, future decision making in a climate of perpetual change. Our research reveals that 86% of industry executives view ‘predictive’ capabilities as their most sought-after features. This means an exciting range of use cases that unlock hidden insights, optimise processes, and drive profitable outcomes can now be achieved.”

In summary, ClicData and Predyktable’s partnership offers Retail and Hospitality brands the tools they need to make informed decisions, outperform competitors, and achieve exceptional results. With a commitment to client success and a dynamic Consumer-Behaviour Engine, they are poised to lead the way in the rapidly evolving world of advanced analytics.

About ClicData

Learn more at www.clicdata.com

ClicData Logo

Why Now? The Perfect Time for Predictive Analytics in Marketing

Posted on by Phillip Sewell

Introduction 

The realm of marketing is in a perpetual state of flux. Emerging technologies, soaring customer expectations, and cutthroat competition have catalysed a landscape that demands nothing short of data-driven prowess. In this dynamic backdrop, the spotlight falls on predictive analytics – an instrumental facet of data science that is set to revolutionise marketing strategies. Predictive analytics leverages historical data to forecast future outcomes, enabling businesses to anticipate demand for goods and services, preempt shifts in customer behaviour, identify trends, and fine-tune marketing campaigns for optimal impact.  

The question that beckons is: Why is now the perfect time for predictive analytics to flourish within the realm of marketing? This is the question that we will be exploring within this blog.  

Predictive Analytics in Marketing with Predyktable

5 Critical Reasons to Adopt Predictive Analytics Now

While there exists a multitude of reasons to embrace predictive analytics, the five highlighted in this discussion stand out as the most relevant and beneficial in the current landscape. These considerations not only address pressing challenges but also offer actionable solutions that resonate with the contemporary needs of businesses. 

  1. The Abundance of Data: The Digital Era has bequeathed an unprecedented treasure trove of data, courtesy of the internet and the ubiquity of mobile devices. This data treasure can be harnessed to train predictive models that unveil accurate predictions about forthcoming behaviours and trends.
  2. The Craving for Real-Time Insights: The rapid tempo of modern business demands nimble decisions to maintain a competitive edge. Predictive analytics can deliver real-time insights into customer behaviour, empowering businesses to make swift, well-informed choices.
  3. The UK skill shortage: The UK’s advertising and marketing industry confronts a significant talent shortage, particularly in data and digital skills. This shortage poses a concern, especially as the UK is the world’s second-largest exporter of advertising services. Predictive analytics can help to address this talent shortage by making it possible for businesses to use data more effectively, analysing data and identify trends and patterns that would be difficult and extremely time consuming to identify manually. 
  4. The Soaring Costs of Digital Advertising: The escalating expenses associated with digital advertising necessitate targeted spending for optimal returns. Predictive analytics aids in precise targeting, enhancing the efficacy of marketing campaigns and yielding superior ROI.
  5. Shifts in the Marketing Tech landscape: This complex intersection of data privacy, technological shifts, and ethical concerns poses a multifaceted challenge for businesses. Two areas in particular stand out as an immediate cause for change:

a. Mitigating Third-Party Cookie Impact: Third-party cookies, instrumental in tracking user behaviour for advertising purposes, face growing scrutiny due to privacy concerns. Browser phasing out of these cookies poses a significant challenge for businesses reliant on them. Predictive analytics offers a remedy, utilising historical data to predict user behaviour patterns, thereby circumventing the dependency on third-party cookies. This enables businesses to create accurate user profiles and preferences for more effective targeting and personalisation strategies.           

b. Adapting to Evolving Social Media Landscape: Recent policy changes on social media platforms, the advancement of platform technologies, and customers who are more savvy with how businesses use their data, are impeding businesses’ data collection and utilisation efforts. Predictive analytics presents an adaptive approach by analysing historical data to identify customer behaviour patterns beyond social, using national mood and consumer opinion from an array of social, economic and industry sources. This insight forms the foundation for targeted marketing campaigns, which can circumvent the changing limitations of social media platforms.  

Predictive Analytics in Social Media with Predyktable

3 Concrete Applications of Predictive Analytics in Marketing

Predictive analytics wields remarkable potential to elevate marketing strategies, and the moment to capitalise on this transformative power is upon us. While the applications of predictive analytics span a diverse range of business domains, it is within marketing where we see an increasing momentum in the application of advanced analytics. Here are three applications where forward-looking marketing departments are adopting predictive analytics.  

  1. Personalising the Customer Experience: By analysing vast quantities of historical data, as well as understanding how current consumer behaviour impacts demand, predictive analytics personalises experiences by suggesting products and services tailored to individual preferences.
  2. Optimising Marketing spend: Optimises ad placement to ensure maximum impact and efficient use of ad spend. Identifies the platforms and channels where high-value audience segments are most active and allocates spend accordingly. By focusing on these channels, predictive analytics maximises reach and engagement while minimising unnecessary ad spend on less effective channels.
  3. Predicting Customer Churn: Anticipating customers at risk of churning allows businesses to take proactive measures to retain them, safeguarding their client base.

These applications are merely the tip of the iceberg in terms of the transformative power of predictive analytics in marketing. To improve marketing outcomes, this tool is indispensable. Beyond these tangible advantages, predictive analytics brings a number of operational benefits to your business. These include:  

  • Risk mitigation: Predictive analytics diminishes uncertainty, guiding businesses toward informed data-driven decisions.
  • Enhanced Efficiency: Automation and pattern identification, streamlines processes, making businesses more efficient.
  • Secure a Competitive Edge: Employing predictive analytics to make informed decisions empowers businesses with an edge over their rivals.

To Summarise 

In the ever-evolving domain of marketing, staying ahead requires proactive innovation. Predictive analytics, with its ability to enrich decision-making, elevate marketing outcomes, and confer competitive advantage, is an indispensable tool. The time is ripe – embrace predictive analytics to navigate the complex currents of modern marketing with poise and precision.

Industry view: what’s really challenging retail & hospitality executives

Posted on by Phillip Sewell

By Phillip Sewell, CEO at Predyktable

I recently conducted a series of interviews with senior executives working across both the retail and hospitality industries to gain a deeper understanding of the most pressing challenges and priorities they currently face.

As these industries continue to navigate an ever-changing landscape, it’s crucial to understand the perspectives of those at the forefront. From supply chain disruptions to shifting consumer preferences, the insights gleaned from these discussions shed light on the most critical issues facing these industries today.

Here are the why’s and how’s behind the tough decisions these senior executives face, with their fascinating insights distilled in a Q&A below.

1- Given the cost-of-living rise and increased costs throughout your supply chain, how will you remain profitable?

“Many CEOs are ex-CFOs, so unsurprisingly they’re dealing with the cost of living by finding ways to cut expenses and remove services – but without damaging sales or losing customers. In fact, across our outlets we’ve reluctantly increased prices by 10% to offset supply chain costs” CIO – Multi-channel Retailer

“As a direct-to-consumer business, we’ve also put-up prices due to a 500% increase in freight costs. We’re now hedging our bets with our supply chain: trying to lock in fixed prices for 5 years to offset the volatile market. We’re also exploring new territories to offset the challenges globally, and where to invest to reduce operational costs.” CEO – Retail

“Customers always want more for less, but prices are going up and promotions are being increased in what has traditionally been a high peak end of season and new season. This is an indicator of how pub and hotel operators are struggling.” MD – Hospitality

Increased prices in retail and hospitality

“As a multinational restaurant chain, we are changing fees to align more to market realities. We need to focus on new business, we’re extending reach beyond our current portfolio – while growing revenue from our existing customer base.” MD – Hospitality

“As a DIY retailer, we need a more agile, flexible supply chain. We’re focusing on what’s driving value, so we’re looking at things like optimising demand forecasting. We are raising prices and measuring the sensitivity of this, while finding ways to reduce supply chain costs. We are also either reducing advert spend or making it work better.” Marketing Director – Retail

“It’s all about price. We’re having to increase prices by 13-14% per annum across our restaurant brands. It’s difficult to get the second visit during the week, so our pricing is keener. It’s a perfect storm of costs and balancing acts.”  Marketing Director – Hospitality

“We have raised prices, but not too much as we’re a price-sensitive confectionery brand. We’re taking a hit on margin and hope it comes back. In the short term, we’re managing costs to mitigate this. It’s survival of the fittest, you try to hoover up market share and hope you retain it in the longer term.” Chief Growth Officer – Hospitality

2- What other issues are you facing today and what are the long-term impacts?

“We must be price sensitive to consumer’s expectations. We’re asking things like what people are willing to accept? How do you quantify the impact service quality has on price points? Managing costs will be critical, and staffing impact in the long-term is a concern. We need to better predict what the labour market will be like in 5 years-time and what changes in our recruitment model can mitigate against this.” CIO – Multi-channel Retailer 

‘Volumes are not where they were, and we’ve been hiking prices. There’s still a role for pubs for informal occasions versus restaurants, but it’s all about getting people through the door.” Marketing Director – Hospitality

man and woman having dinner at restaurant

“It’s all about where to find new business. Customers are no longer loyal, basically businesses are just “swapping” customers and not stimulating new growth. We need new revenue and new customers.” Digital Transformation Director – Retailer

“Online will not hold the dominance it once did as the cost of online is becoming less feasible and concerns on the environment increase. We may see a shift back to bricks and mortar to deliver a greater experience.” Global VP of E-Commerce – Retailer

“There is a danger of oversupply in the market for restaurants. After many closures during covid, there’s been some aggressive new openings with new operators mostly in city centres. I think there will be an implosion. Pubs have really got their act together and are well placed to challenge restaurants, they also suit people when they’re working from home.” Chief Marketing Officer – Hospitality

Recessionary impact and labour availability are big issues. Everyone in the industry is suffering, with chefs being the most difficult to recruit. We’re using some central kitchens to produce food consistently and reduce the impact at restaurant level.” Chief Growth Officer – Hospitality

3- What are your key priorities and investments over the next 3 years?

“Technology investment is key. We’re examining which technologies can return ROI – while solving the biggest problems we have. We do need to better understand which areas require investments to plug the leaks in costs.” CIO – Multi-channel Retailer

“Digital tools and online is one area of investment for us, coupled with systems to help labour scheduling. It’s all about making the central and pub teams become more efficient. Capex is being maintained, but it’s now focused on maintenance and improvement or conversion to new offers – rather than new builds.” Marketing Director – Hospitality

“We’re focusing on improving the supply chain. It’s the biggest cost centre and has the biggest negative impact on customer experience. Over 45% of customer care calls cover where is my product? So, having a fantastic supply chain would help address this.” Digital Transformation Director – Retailer

“We’ll be investing in systems including ERP, PIM and re-platforming, to reduce the friction of doing business and enable scale and agility. Improving staff wellbeing is also key, especially as the fight to retain staff becomes increasingly critical. We are improving performance marketing that better connects with customers. Acquisition will also prove key, as the competition becomes increasingly fierce.” Global VP of E-Commerce – Retailer

“We’ll be driving like for like sales, including investing in the fabric of the building or in-restaurant technology that hits our sweet spot. Potential acquisitions are a consideration, with a focus on small operators with decent brands and locations. We’re also trying to find the sweet spot of recruitment and we’ll invest when we’ve got it right.” Chief Marketing Officer – Hospitality

Staying relevant and interesting is core to our strategy. We need a competitive edge versus competitors, so we’ve got to work out what that is and then make it relevant.” Chief Growth Officer – Hospitality

Final thoughts

The COVID hangover means that everyone still has a short-term mentality. That is the sentiment from all those I spoke with. Profitability is now the short-term goal, rather than longer-term strategic planning that existed pre-COVID.

So, with key decisions on spend, labour optimisation, demand forecasting and more, how about the efficacy of current solutions that support decision-making?

All agree that business intelligence and data analytics have helped retail and hospitality executives understand and influence their customers’ buying habits – but only up to a point.

Despite billions of pounds spent globally on data platforms, data repositories and a whole stack of tools, most still lack the help they need to turn data into forward actions that maximise profits. Everyone agreed that more ‘prescriptive’ data insights are urgently required by brands: providing forward recommendations that support more profitable business-critical decisions. 

Why smart retailers are checking out prescriptive analytics

Posted on by Phillip Sewell

“Most retailers are overwhelmed with vast data volumes offering little or no recommendations on what it means to them.” says Predyktable co-founder and CEO Phillip Sewell

For many retailers trying to navigate a climate of perpetual change, making correct business-critical calls on complex environmental, economic and consumer future outcomes is an expensive gamble. This is because current business intelligence and data analytics approaches that support retailers’ decision-making, no longer cut it.  

Traditionally, business intelligence and data analytics have helped retailers understand and influence their customers’ buying habits. But despite billions of pounds spent globally on data platforms, data repositories and a whole stack of tools, most retail professionals still lack the support they need to turn data into forward actions that maximise profits. 

Most retailers are overwhelmed with vast data volumes offering little or no recommendations on what it means to them. Many also use solutions heavily reliant on historic data and insights that aren’t tailored for their specific forward-thinking needs. There’s not enough focus on identifying and understanding wider external data sources. This manual time-consuming research isn’t being done, so the data quality and depth aren’t there to support accurate predictions.  

These approaches aren’t enough to help retailers form a clear future view and know what to do about it.  

A forward-looking catalyst 

To solve these issues, there’s an increasingly sophisticated capability that’s taking data analytics way beyond explanations and predictions. Welcome to ‘prescriptive analytics’, which is widely considered the fourth stage of data analytics’ evolution. Here’s where it sits:  

  1. Descriptive analytics – what happened?
  2. Diagnostic analytics – why did it happen?
  3. Predictive analytics – what might happen in the future?
  4. Prescriptive analytics – what should we do next?

Prescriptive analytics aims to look into the future and then recommend the best course of action.  

Marks & Spencer and John Lewis are among a growing number of retailers using prescriptive analytics to ‘look into the future’ and pre-empt trading conditions in the weeks, months and years ahead. For example, M&S uses this approach to guide its design, buying and pricing decisions across thousands of product lines in 50 categories, including apparel, lingerie, footwear, accessories, food, home and beauty. 

Why prescriptive analytics delivers more as a managed service 

When it comes to outsourcing this capability, many retailers miss out by working with conventional data providers offering prescriptive analytics as a bolt-on, one-off piece of work – with minimal support. I believe that achieving valuable results with prescriptive analytics isn’t possible with off the shelf or piecemeal solutions that treat retailers as commodities.

It’s better opting for a partner offering prescriptive analytics as a fully managed service, backed by retail sector experience. They must focus on understanding a retailer’s business and specific challenges – as these are crucial factors underpinning success. Retailers must also be supported every step of the way, so they keep solving new challenges facing their business. 

The best prescriptive analytics services blend descriptive, diagnostic and predictive insights, with cutting-edge artificial intelligence, machine learning, automation, genuine data science and in-sector consultancy expertise. Everything should be custom built, with each step creating prescription models precisely choreographed to meet retailers’ individual needs.  

This means enhancing internal data, with much wider external insights including global & local trends: weather, travel, localised demand spikes, and more.  Using this high-quality data, data scientists build and optimise prescription models which identify previously elusive, connected, patterns to deliver the most accurate foresight fuelled prescriptions.  

Expect data scientists to continually find new insights to keep models relevant, while learning from the data so they keep delivering value. By uniquely aggregating data from a wider range of external sector sources, models are further enriched to provide greater accuracy and depth to foresight, so the prescription models keep getting better and retailers keep making the most profitable business decisions. 

Use case – customer sentiment  

Here’s an example of how retailers can better gauge brand sentiment through the voice of the customer with prescriptive analytics.  

Current analytics tools offer limited views on what’s being said about brand, as they mainly focus on social media analysis and sample surveys. They don’t show how retailers are perceived through all online and offline touchpoints. By not involving sentiment in predictions, means less accurate, decision-making.  

A better approach is to create machine learning models connected to everywhere that customers are talking about the brand. This means covering online and offline channels, social media platforms, rating & review sites, search engines, contact centre logs, chat bots, blog posts, and more.   

Natural language processing is then used to contextualise each interaction. This means establishing if it’s voiced as a positive, neutral, or negative opinion, if this opinion is shared by anyone else, and if so, what’s the commonality between them?    

Sentiment and activity hotspots are gauged across customer segments, location, and channels. These insights are enhanced with domain models that track behaviours at a national and regional level. This means determining if brand sentiment is part of a wider opinion shift, or if it’s unique to customers – because of a retailer’s actions.   

All this activity generates rich foresight that fuels recommendations on which new products to launch or territories to explore. By also dynamically forecasting demand, enables retailers to optimise the cost of entering new customer segments.   

What gains can prescriptive analytics deliver for retail? 

There’s huge value and so many positive outcomes to be gained with prescriptive analytics as a service, some of these include:  

  • Know which areas to reduce cost: including marketing spend, labour optimisation and demand forecasting.  
  • Understand exactly where to make more money within the most profitable customer segments. 
  • Identify which customers are most likely to convert, then win them over with a hyper-personalised and engaging shopping experiences. 
  • Retain high-value customers by recommending products and services that complement customers’ existing purchase history, interests and lifestyle.  
  • Better optimise pricing at a regional level to maximise the profit opportunities. 

Final thoughts

Whatever your size, Predyktable delivers prescriptive analytics as a fully managed service to generate actionable foresight faster, without complexity and compromise. To discuss how we can help your organisation make more profitable decisions, please drop us a line, we’d love a chat.