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In times of COVID-19, best practices for generating on-line demand for Fashion and Department Stores

Updated: Sep 25, 2020

Abhinav Chandra, CEO and Founder PredictSys Inc

April 6, 2020

Since March 19th 2020, when California issued a statewide shelter-in-place order in response to COVID-19, the majority of US states have followed suit and today at least 90% of the US population is under some sort of shelter-in-place order. For the majority of retailers nationwide, especially softlines (clothing/shoes/jewelry) retailers and department stores, this has resulted in temporarily closing physical stores and a renewed focus on eCommerce operations as the primary means to drive sales, with widely varying success. We at PredictSys Inc. used advanced technologies and analyzed Big Data to answer WHY. Our analysis shows that those retailers performing better than others in these circumstances are the result of clearly articulated, specific best practices that are driving superior performance.

Prioritize Engagement


The focus for retailers, while brick and mortar stores are closed, is to move as much inventory as possible through eCommerce as to maintain cash flow. Retailers are looking to increase both Reach (traffic) and Engagement (page views per visit) on their websites. Reach has declined in softlines as consumer focus has shifted to prioritizing the procurement of essential goods during high unemployment, leaving softlines retailers with relatively more control over Engagement as compared with Reach. Therefore, operational choices focused on increasing Engagement have a larger impact. Accordingly, our data shows that top performers in the department store market segment have seen customer Engagement increase by more than 20% compared to last year, whereas department stores slow to adopt an Engagement focused strategy have seen Engagement decrease by more than 20%.


Best Practices to increase Engagement


Our detailed analysis highlights five best practices that have resulted in the strongest Engagement performances:


1. Run broad promotions

Most retailers with high engagement are running broad promotions online, including brands and categories that are not promoted traditionally, to draw in a broader audience and encourage additional spend. Strong, broad, and clearly articulated promotions help break into these expanded audiences and are essential to increasing Engagement.


2. Strengthen free shipping offers

Paid shipping is a disproportionately high barrier to conversion. Most retailers in the high Engagement category are offering free shipping for orders above $25. A higher minimum purchase threshold is showing to be especially prohibitive to Engagement and ultimately conversion. Beyond that, retailers should also evaluate their ability to offer “Free Shipping on All Orders,” as at least one top performer has done.


3. Clarify promotional messaging throughout the site

Offers must be simple and clear. Shoppers are currently emotionally overloaded so it’s vital to keep messaging direct and relevant. Take the opportunity to highlight “Free Shipping” at every step of the customer journey.


4. Simplify promotional navigation

High performing retailers have made it easy for customers to easily and quickly reach promotional items from anywhere on the site.


5. Highlight your competitive advantages

Prominently displaying the retailer’s competitive advantage results in increased Engagement leading to an increase in conversion. As an example, if you automatically price match, make the messaging explicit that customers are getting the lowest price.



Increase Reach


On the other hand, Reach (measured as the change in unique visitors year-over-year) has declined overall across softlines retailers by more than 20%. As mentioned earlier, this industry-wide decline is driven primarily by customers prioritizing essential goods during this time of crisis and uncertain employment. Our data shows that the magnitude of decline in Reach varies across softlines retailers; for example, specialty stores focused primarily on men’s tailored clothing are seeing the sharpest declines of more than 50% compared to last year, while broader department stores on average are seeing declines of 23%. Within the department store segment, there are still major variations. For example, one upscale nationwide retailer has experienced a 6% decline in Reach vs. another that is experiencing a 30+% decline. Obviously attempting to address the industry-wide COVID-19 induced decline is futile, however, there are three best practices to be gleaned from retailers seeing the smallest decreases.


1. Utilize your full marketing toolkit

Highlight your strongest, clearest promotion to customers through social media and Influencers, as top performers are seeing their share of traffic from these channels increase.


2. Audit and strengthen your affiliate strategy

Review and ensure that top referral sites and Influencers are incentivized to link back to your strongest promotions, as top performers on average had 15%+ more top sites linking to them vs. the stragglers.


3. Refine and personalize your email messaging

Tried and true messages and promotions may not be appropriate for your customers right now. Highlight products applicable to home confinement and video calls (e.g., tops rather than bottoms) and ensure customers are receiving relevant messages – now is the time to ramp up personalization if you haven’t done it yet.



Plan for the future


These recommendations are some quick best practices to boost eCommerce sales in the short-term. Retailers should plan for what the demand pattern will look like under different scenarios in the future; for example, if restrictions stay in place for longer, or if the shelter-in-place orders are lifted. At PredictSys, we continue to develop a range of models based on these, and more, scenarios to predict demand and to help our clients plan.


Got questions? I can be reached at abhinav@predictsysinc.com, and our team is ready to help with any challenges.


PredictSys, Inc. uses Big Data and Advanced Technologies such as AI, machine learning, and customer sentiment analysis to improve fashion forecasting and to generate automated profit and customer experience optimization recommendations. Our team includes Data Scientists, Merchants, Planners, and Digital/Omnichannel experts.


Abhinav Chandra, CEO and Founder, brings more than 20 years of retail and technology expertise to PredictSys. His experience includes Head of Women's Clothing (Amazon), Head of Customer Experience (Amazon), and Associate Partner in McKinsey & Company's Retail Practice.

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