The best way for retailers to maximise their benefits on Black Friday is to optimize their pricing. Here, you’ll find practical tips about price setting and pricing strategy, including high-impact dynamic pricing solutions based on machine learning technology.
Black Friday and Cyber Monday hail from the USA, but they have since made their way to Germany, offering shoppers the best deals of the entire year. Black Friday takes place on the Friday after Thanksgiving, meaning that in 2020, it will take place on November 27th. Cyber Monday will take place the following Monday.
Both days are particularly important for online stores. According to a survey by Statista conducted in 2019, over 90% of the consumers surveyed were familiar with Black Friday, and a good 43% of them also intend to purchase discounted products on that day. In recent years, online purchases and thus turnover on both days has increased continuously. In the USA alone, they amounted to 7.4 billion US dollars on Black Friday in 2019, and even around 9.4 billion US dollars on Cyber Monday. Even in Germany, consumers planned to shop for more than €200 per capita on Black Friday 2018. In Germany, the expenditure on both days in 2018 reached a volume of around €2.5 billion.
In 2018, high on the Black Friday shopping list in Germany were clothing and shoes (35%), care and beauty products (15%) as well as films, music and video and computer games (11% each).
Source: Statista Dossier “Black Friday and Cyber Monday”
While 43% of respondents said that they had been looking at Black Friday and Cyber Monday for some time, 40% of those surveyed were spontaneous. With the right pricing strategy and Dynamic Pricing, both customer groups can be targeted.
Retailers who want to profit from discount battles need an effective, well-thought-out pricing strategy, and that means that it’s good to get started a few weeks in advance.
Banners and pop-up reminders on your website like “Almost sold out!” Or “Only one left” convey urgency, so we definitely recommend using these on Black Friday.
„The best offers are overstocked bestsellers with a somewhat modest discount and discontinued products with a better discount. It all has to fit with your branding strategy and focus on acquiring new customers and rewarding existing customers. Flat discounts seem lazy and desperate, which will hurt your brand perception.” Matthew Dean, VP Digital, Worldwide at HUGO BOSS
And last but not least: avoid price increases directly before Black Friday. Targeted price changes at this critical time can be off-putting for customers. If you need to increase your prices, do so in October.
Retailers who want to stay ahead in terms of sales and profits on Black Friday need to leverage the full potential of their data to optimize pricing. A deep understanding of customers’ price elasticity is critical, and that’s exactly where advanced pricing software can support retailers with dynamic pricing. This software measures the price disposition of customers and automatically suggests the optimal discount for each product. This way, retailers can ensure that their pricing strategy exploits their full margin potential.
With advanced pricing software, you can simulate various price scenarios for individual categories, forecasting revenue, sales and profit outcomes for your respective targets. Pricing software also makes it possible to employ different strategies for selected categories which are expected to sell out quickly, for example.
Advanced pricing software uses machine learning so that retailers can capture unique customer behavior and thus improve their pricing. The machine learning algorithms are used to calculate products’ price elasticity based on data gathered from past sales activities, such as those from Black Friday in 2019. In other words: sales volume and all the relevant influencing parameters that go into achieving them – from the competitors’ prices to weather and seasonality – are all factored in by the software when calculating optimal prices. Compared to the more traditional rule-based pricing, dynamic pricing offers highly accurate predictions and enables differentiated, smart price setting, which in turn leads to higher revenue and profits for retailers.
You can find more information on machine-learning-based pricing here.
At 7Learnings, we have more than 10 years of experience with machine learning technology. Leading European online retailers use our technology to optimize their prices. On average, we have been able to increase our clients' profits by more than 10% and prove it in A/B tests. If you want to learn more about the potential of next-generation dynamic pricing, feel free to contact us to arrange a product demo.
Download our whitepaper to learn more about the advantages of predictive pricing for retailers.