How to Increase Speed-To-Market with Efficient Competitor Analysis

How to Increase Speed-To-Market with Efficient Competitor Analysis

How to Increase Speed-To-Market with Efficient Competitor Analysis

As the fashion landscape becomes increasingly competitive and consumer preferences rapidly evolve, brands need to accelerate their speed-to-market to capitalise on demand ahead of their competitors. To do this, they require market and competitor analysis to identify demand and support any strategic business decisions. 

Brands typically perform comp shopping to study competitors’ activities and to gather market information. However, the conventional way of surveying stores in person or browsing through competitors’ sites online is time-consuming and lacks complete market visibility. 

Over the years, the number of new brands and the speed at which these brands shift strategies has increased tremendously but the conventional way of analysing competitors is not optimised for the current retail landscape.

This makes brands vulnerable to blind spots in the market, hindering them from a comprehensive understanding of the market.

To combat this, fashion market insights offer brands deeper visibility into competitors’ product performance, backed with data and accurate information so opportunities and gaps can be identified immediately.

Consolidated data from all over the web allows brands to practice comp shopping digitally within seconds – making the process more efficient while accessing even more information than before.

Here, we have laid out a 5-step process to analysing competitors effectively, providing brands with clear insights into market trends and how their competitors are responding.

Step 1: Identify a List of Competitors 

Firstly, as with the conventional way of comp shopping, we begin by identifying an extensive mix of competitors. The brands or retailers you would need to monitor are those who: 

  • Sell similar products in the same fashion segment
  • Operate in the same market
  • Share similar consumer demographics
How to Increase Speed-To-Market with Efficient Competitor Analysis - Brands grouped by the fast fashion segment on the Omnilytics Dashboard.
Image Source: Brands grouped by the fast fashion segment on the Omnilytics Dashboard. 

In this example, we’ll be comparing two competing online fast fashion brands, Fashion Nova and Asos Design.

Step 2: Compare Trade Performances

How to Increase Speed-To-Market with Efficient Competitor Analysis -  Trade performances of Fashion Nova and Asos Design in the month of May 2020.
Image Source: Trade performances of Fashion Nova and Asos Design in the month of May 2020.

To understand which brand is outperforming the other, we compared their trade performances over the period of a month on assortment size, new-in rate and sell-out rate. 

Looking at the month of May, Asos Design consistently had a higher SKU count compared to Fashion Nova, with the biggest difference captured in the third week. 

How to Increase Speed-To-Market with Efficient Competitor Analysis -  New-in rate vs total products for Fashion Nova and Asos Design.
Image Source: New-in rate vs total products for Fashion Nova and Asos Design.

Despite having a smaller SKU count, Fashion Nova contributed a larger percentage of newness, averaging at 2% every week while Asos Design’s fluctuated between 1% to 2%.

How to Increase Speed-To-Market with Efficient Competitor Analysis - Full-price sell-out rate for Fashion Nova and Asos Design.
Image Source: Full-price sell-out rate for Fashion Nova and Asos Design.

Looking at the full price sell-out, Asos Design had lesser full-priced products compared to Fashion Nova. The former had a strong trading period from May 1st to May 14th as sell-out increased gradually up to the third week, followed by a decline in the next week. 

On the other hand, Fashion Nova had a consistent sell-out performance throughout the month, leading to a small spike in the fourth week of May.

These insights can inform the right rate of newness and assortment size required to achieve the targeted sell-out rate.

Step 3: Analyse Differences in Pricing Strategy 

After understanding the right volume of SKUs to stock, the differences in pricing strategies are studied to find out which price point is converting the highest sell-out. 

Price breakdown for Fashion Nova and Asos Design.
Image Source: Price breakdown for Fashion Nova and Asos Design.

The bulk of Fashion Nova and Asos Design’s assortment is priced at under $50. However, each brand has a different approach to determining the right number of SKUs for every price range. 

Based on the chart, Asos Design priced the majority of its assortment between $10 and $29. Meanwhile, Fashion Nova had a more balanced SKUs stocked across the $10 to $39 price range. 

Price breakdown vs sell-out for Fashion Nova and Asos Design.
Image Source: Price breakdown vs sell-out for Fashion Nova and Asos Design.

In the analysis of price breakdown against sell-out, both brands showed signs of understock at the $0-$9 price range, the sell-out rates far exceed the number of SKUs available. Conversely, Asos Design’s $10-$19 range showed signs of overstock as sell-out fell below 30%.

Based on this evidence, the optimal number of SKUs to stock for each price range can be identified to avoid an overstock or understock situation and convert higher sell-outs.

Learn more about this topic: Spotting Category Opportunities in Assortment Planning

Step 4: Understand Product Phasing Patterns

For the next step, each brand’s product phasing patterns were compared by studying the number of SKUs launched as a new-in or placed on discount. These insights help to decide the best time to launch new arrivals or to begin or end a markdown activity. 

How to Increase Speed-To-Market with Efficient Competitor Analysis - Product phasing for Fashion Nova and Asos Design from July ‘19 to June ‘20.
Image Source: Product phasing for Fashion Nova and Asos Design from July ‘19 to June ‘20.

Based on the chart, Fashion Nova had a huge spike of new-ins in February ‘20 coinciding with Spring Newness, followed by another spike of newness starting May ‘20 as it pulled back on discounting SKUs significantly.

The brand also had two major markdown periods in the timeline. A major markdown occurred in December during the holiday season with more than 4,000 SKUs discounted and another heavy markdown period in April with 3,450 SKUs discounted. 

The second chart shows Asos Design had a notable spike in newness in August as it began stocking up on Fall products. This was followed by a markdown in September during the back-to-school period and another in starting November for the holiday season. Similar to Fashion Nova, Asos Design also planned a major markdown in April.

The evidence shows both brands managed to avoid major overlap in markdown periods or newness launches aside from December ‘19 and April ‘20, allowing them to decrease the potential for direct competition and maximise sell-out.

Step 5: Compare Against Own Performance 

Based on the data compiled, generate a competitor analysis report and compare against your own performance to identify any missing gaps or opportunities for immediate actions. 

Effective Competitor Analysis 

Competitor analysis should be executed at least once a month, if not more frequent, to identify market trends or opportunities in a timely manner. Benchmarking trade performance against competitors’ gives a holistic view on market positioning, giving you the agility to navigate the retail landscape.

With a comprehensive competitor analysis routine, you can build an archive of insights to back strategic decision making in the next merchandise planning season. Only by acquiring accurate data insights on the competitive landscape will you make informed merchandising decisions and gain a strong foothold in the market.

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