Retailers resort to promotional markdowns for many reasons. They usually play an important role in product lifecycle management and can sometimes be a necessity to help sell end-of-season, outdated, or slow-moving merchandise.
Unfortunately, retailers often use promotional markdowns as a strategy to generate revenue and to drive consumer demand.
While you may see a short-term lift in traffic and sales, retailers should tread carefully around promotional discounts. It can be a formula for stagnating sales growth, diminishing profit margins, and it can negatively impact brand value.
Retailers are living in an era of intense competition, growing demand for consumer price transparency, and fast-moving fashion trends. It can be hard to keep up. To compete with other retailers with identical consumers, some may feel the need to resort to lower pricing to remain competitive.
Meanwhile, some brands rarely offer discounts, such as Apple, as they have established themselves as the best in the business and have a very high level of consumer loyalty. High-end luxury retailers also avoid promotional markdowns. They know that exclusivity is a key element in driving their consumer equity, so offering discounts may create a perception of cheapening.
However, we can’t all be Apple.
Even if you’re unable to use a competitive advantage such as superior products or services, location or social status, you can still use your data as an advantage and leverage advanced markdown solutions using segmentation and predictive data analytics.
Custora’s experience working with over 100 retailers has given us insights into alternative strategies to drive revenue, retain and acquire customers, and set optimal discounts without devaluing your brand. And we’d like to share those insights with you because sharing is caring.
We have four tried-and-tested strategies to help you compete in today’s market without slashing prices:
- Balance merchandise and marketing priorities using affinities
- Set optimal discounts to achieve a positive ROI
- Shift your focus to high-value customers
- Determine price sensitivity versus discount sensitivity
We can’t give away all of our customers’ secrets, so to keep their information confidential, some of these companies and figures will remain anonymous.
Balance merchandise and marketing priorities using affinities
In the retail world, marketers can either take a user-first approach, in which you focus on the customer’s preference as the primary input for specific product categories, or a product-first approach, where the product is the primary input for personalization. Both strategies are effective for moving stock, as long as the correct customer affinities and segments are determined.
Marketing with product affinities can have a powerful impact on the customer experience and bring in revenue
According to a 2018 report, ‘Connected Consumer: How Consumers Shop and Buy Clothes’ by pymnts.com, the types of consumer experiences most merchants spend a lot of their time on — like social media prompts, having a fun in-store experience, and order tracking, among others — barely captivated any interest among the 2,035 survey participants. Instead, existing customers said they valued a retailer's ability to personalize offers that would reflect their buying preferences.
Marketing with product affinities can have a powerful impact on the customer experience and bring in revenue. Rather than marketing broad recommendations to your customers on what they may like based on previous purchases, retailers can stay one step ahead by using predictive affinity modeling to identify propensities of customers who might be receptive to a given product (even if they haven’t bought it yet).
You’ll not only reduce your reliance on discounts but also have the added benefit of spending less on retention campaigns using this strategy. Once your customer affinities are determined, you can then automatically stream this information into your marketing channels, so your customers will continuously receive up-to-date and relevant product recommendations — without the manual process of uploading CSVs.
We’ve seen this in action. An established global retailer used advanced segmentation and predictive affinity modeling to send personalized product recommendations via a monthly direct-mail campaign that targeted churning, high-value customers.
Within the first month of starting this campaign, this retailer saw a 145% lift in revenue per recipient and a 97% lift in conversion rate. Not bad for a month’s work.
The challenge with affinities usually lies within the vast range and complexity of data, and the ability to take advantage of key information and incorporate this into your personalized marketing strategy.
However, once your marketing team has mastered the important customer insights with the help of your CRM team or third-party providers, you will be able to offer more of the right products to your shoppers at the critical moments before and after the conversion stage — without resorting to lower prices to move stock.
You can also use advanced affinity modeling to sell stock as part of a strong cross-team collaboration with your merchandise team.
For example, it’s springtime and your merchandise team has a priority to sell floral dresses. You can promote this to a vast majority of customers, maybe you could even segment by gender or target a warm location. Or you can go deeper and choose to fully utilize your customer profiles.
With a deeper understanding of your data insights, you can quickly surface the customers who are not only really into dresses but are also early adopters of the latest trends. Then you can target these customers with email, Facebook, and display ads to get the most out of each new product arrival.
This method also creates an effective replenishment strategy. For example, a national footwear retailer completed a robust analysis on the typical timeline of when people re-purchase running shoes and then set up a trigger to send personalized email campaigns to target segments with a particular affinity for running shoes. For other styles that need to be replaced, their marketing team is now equipped to target the right buyers with correlating affinities to keep a consistent turnover, so stock doesn’t become quickly outdated and discounted.
Set optimal discounts to achieve a positive ROI
Of course, most retailers won’t be able to completely avoid promotional markdowns. There is, after all, a direct correlation between inventory turnover and discounts. So, the next best thing is finding your target audience and discovering the optimal discount percentage. This will keep your bargain shoppers happy, your inventory team happy, and you will avoid selling products too cheaply.
As with most marketing initiatives, you need to test, test and test again. Start with segmenting the customers that love to shop a bargain and also have an interest in the product you need to sell, so you can ensure you are delivering the right message to the right people.
Then, you can upload this target list in your Email Service Provider (if your data is not already integrated with your ESP) and test your promotional markdown campaigns. The ‘winning’ message can then set the optimal discount for your promotional item.
Custora customer and top shoe manufacturer Crocs successfully executed this promotional tactic. Crocs streamed their targeted segments into all their marketing platforms and tested various forms of messaging.
With quick and easy access to the campaign results, their marketing team uncovered the optimal discount percentage for their customer segments. Now they can offer a promotion that moves stock but also results in a positive ROI.
Shift your focus to high-value customers
Some retailers may be too fixated on how to increase the AOV of those customers that only buy on discount — when in fact they should be focused on retaining their better customers. The top 5% of the customer base can account for 30-40% of revenue*, so once you redirect your marketing efforts towards the top value customers, you’ll find that these are the ones that impact the bottom line.
According to a recent survey by Revionics, 52% of weekly or monthly promotions go to customers who would pay full price. With advanced segmentation modeling, retailers can find their high-value customers and remove them from promotional markdown marketing campaigns. Then you can test alternative personalized messages to engage and reactivate buying behavior such as emerging trends or popular products.
At Custora, we have seen our customers successfully execute this strategy and generate desirable results. We currently work with a popular furniture retailer that previously offered discounts to everyone in their database before they used Custora to segment high-value customers. In just one (but smart) initiative, this retailer removed the ‘value’ banner featuring low price point items on their email campaign for high price point customers, resulting in an impressive $118k lift in profit margin.
Once you’ve discovered who your high-value customers are, it is time to increase your database with customers that display similar attributes. Using audience tools like Google Adwords, Facebook or Liveramp, you can find lookalike audiences.
Or with platforms like Custora, you can also use predictive lifetime value models to identify customers most likely to be in the top segment before they spend enough to reach this top level. That way you can engage and retain people showing signs of VIP customer behavior as if they already were VIP customers.
This strategy was put to the test. A well-known brand based in California saw their cost-per-click go up over time and acquisition slow to a halt. To resolve this, they extracted their high-value customers and then pushed that into Google match to discover look-like audiences. With helpful audience tools like Google custom match and the ability to leverage customer segments, this retailer saw an immediate boost on ROAS in their paid search and inbox ads.
Determine price sensitivity versus promotional sensitivity
Some shoppers are bona fide bargain hunters. They are the ones that will buy from your store during a sale or when an item is discounted. Others can be price-sensitive, they prefer to buy at a lower price point.
Determining your price and promotional sensitive segments can be quite useful for retailers. Consumers are largely driven to switch brands because of price points. It is best practice to know your segments, so you can appeal to everyone and personalize their experience.
As seasons change, you may be asked to promote a spring clearance on sweaters. To effectively clear stock and personalize your marketing message, you can segment your audience by customers with an affinity for sweaters and who are promotionally sensitive—i.e. only buy on discount. On the flip side, with everyday low priced products, you can target your price-sensitive customers.
We work with many retailers that use high price points at a discount versus low price basics to drive a higher engagement and conversion rate. Some retailers use direct mail segmentation for their 'price point gift guides', while others will target the right audience for their ‘value week’ emails.
And now for my final thoughts...
Mindless markdowns should be a last resort for retailers wanting to increase revenue and clicks and bricks traffic. We know that there are many reasons for markdowns — some factors cannot be controlled, while many others can.
For the factors that can be controlled, it’s important to strive to deepen your knowledge of your customers to create a personalized engagement that will drive conversions and revenue.
Whether this be personalized product recommendations or deciphering the influencers and the discounts that shape behavior, you can successfully draw more transactions and expand revenue to your physical and virtual store without compromising your profit margins.
So, instead of driving consumer demand with promotional markdowns, let your data be your strategic asset to create brand value and build an advantage in this ultra-competitive environment.
*Source was taken from our book ‘One and (Not) Done’. You can read more about how to leverage customer analytics to address the one-time buyer problem here