Today’s retailers have access to vast stores of data that allow them to create the personalised retail experience that customers have come to expect. Used in the right way, analytics can be the key to bringing customers in through the door, building a better online experience, or simply helping weather slow periods by enabling faster, more efficient and nimble supply chain changes.
Interestingly, customer perceptions towards a brand can significantly change following Black Friday discounting and January sales. Pricing strategy can be confusing at the best of times. Given the option of £50 off on a high-value product compared to a 70 percent discount on a low value item: which is the better offer? Which deal do consumers trust, and why? More importantly, how does it impact the brand perception?
One thing’s for sure: brand loyalty and consumer trust are no longer guaranteed in today’s fast-changing retail environment. Retailers must find alternative ways to engage with consumers.
The dark art of forecasting
For years, retailers have collected customer data through loyalty cards, email marketing promotions, point-of-sales tills, as well as online browsing behaviour and purchase orders. What has changed over the years is the technology that allows retailers to analyse and understand data. The advent of technologies like Hadoop has enabled the development of advanced analytics solutions to produce more insightful and timely answers for retailers, which is of huge value during peak trading seasons.
Another interesting point here is that often the data collected spans the last three years of trading or more. This is traditionally used by store managers to forecast pricing and demand. Yet we know that outdated historical data, coupled with unpredictable external factors like weather conditions, regularly produce inaccurate forecasts.
As a result, retailers are still making predictions largely based on gut feel rather than objective insights. More often than not, they are also spontaneously reacting to competitors’ price cuts without carefully calculating their profits and loss potential.
Brands switch off
Another common retail pitfall is the effect of over marketing with a general blanket message. Unaware of the consequence of blasting out daily and sometimes twice-daily promotional emails in the hope of catching shoppers’ bargain hunting instincts, retailers are actually turning customers away. Consumers will easily unsubscribe from brands they previously loved, especially if they feel they are bombarded with irrelevant and unwanted product recommendations that only clog up their inboxes.
True personalisation demands an intimate understanding of the customer, and willingness from the individual to participate.
One of our retail customers has been using data analytics to deliver personalised product displays. These are highly targeted to improve conversion and avoid endless page scrolling. Instead of feeling like every other shopper each time a customer enters the site, they can now enjoy a genuinely personal engagement with the retailer. Behaviour is predicted and product recommendations are based on browsing, and a wealth of customer and transaction data.
With a more personalised customer experience, shoppers will be able to purchase products at the best price, while receiving the best in-store, online and post-sales service.
As retailers have better insights into customer behaviour and spending patterns, they will be able to personalise the experience and product recommendation. In turn, shoppers will feel they are receiving better deals and being looked after by the retailer. Some customers may also find themselves receiving extra benefits or upgrades through loyalty schemes, enhancing the overall experience with the brand.
SAS has worked for many years with dunnhumby, the power behind Tesco’s Clubcard. Today there is a need to market to customers across multiple channels. SAS has also worked with Callcredit Information Group, specialists in marketing services, analytics and data, to deliver a market leading omnichannel marketing and analytics service. This partnership has delivered a solution to ASDA. It provides an easy-to-use interface, with repeatable processes to enable organisations to deliver more campaigns – from simple to complex – in a shorter space of time.
Sail through the online retail revolution
On Black Friday alone, shoppers spent £1.1 billion with UK online retailers, setting a new internet retail record which underlines the online shopping revolution. The true impact of this year’s trading results are yet to be seen but one thing is certain – retailers can no longer rely on historical data alone to forecast pricing models or stock performance.
The cost for retailers can be drastic if they cannot accurately analyse the net profitability impact ahead of the peak trading period.
Big data enables retailers to more accurately forecast actual consumer demand, based on the very latest fashions and trends, as well as the timing and the likely location for that demand. For example, big data can be used as follows:
- Analyse the data and visualise the demand forecast on a specific product in a specific store on a specific time and day of the week. This enables the retailer to ensure they get specific stock to that location.
- Predict what else the customers might like to buy in the same transaction and personalise the product recommendations accordingly.
- Predict the behaviour of customers by channel. For example, how customers might move between online browsing and in store purchasing, or their preference for home deliveries or Click & Collect.
- Use demand insight to negotiate more effectively what the retailer buys from suppliers and when. Also, strategically plan for a more coherent and cheaper supply chain and transportation journey, allowing for external factors like extreme weather conditions.
- Understand which segment of the customer demographics are most valuable to the business and devise a more effective way to nurture their spending and relationship with the brand.
- Delight your customers by presenting them with product and brand recommendations which you already know they will want and like.
In principle, the knowledge of who wants what and when is an art form in retailing that is rooted in the golden era of advertising and knowing your customer. Retailers that have enhanced their skills in this area will continue to grow and prosper, which is why demand for data analytics technology will continue to grow over the coming years.
Find out more about how to make effective pricing decisions.
Unlock your retail potential with better pricing models and brand loyalty was published on Customer Intelligence.