The operation of business only works when consumers’ demand exists to correspond with supplied products. Companies may conduct investment in branch locations or attractive marketing promotions, but customers’ product preference is still the core determinant of companies’ sales. If products do not match their interest or demand, customers will not consider to make a purchase then leave the store and may never return.
The competitiveness on eCommerce shopping platforms creates tension among online retailers when the distance among them is just a few clicks. The winning competitor in this market is the one to understand different types of customers’ behavior with an effective assortment optimization.
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According to NRF holiday shopping data, 77% of Customers leave a store 4 times meaning retailers missing 4 opportunities to close the deal. The common reason is that 67.3% of them couldn’t find the demanded products then ended up driving to other competitor stores. For example, customers might leave when they didn’t find the right color and size or when their desired merchandise was out of stock and not available in display and that number surprisingly accounted for 66.3%.
Moreover, the number of supplies in holiday shopping season usually experience a rocket in which may leave customers in confusion and chaos if products are not clearly categorized. For this reason, a proper assortment to these supplies are in high demand.
In retail, the strategy of assortment is a product planning process, in both brick-and-mortar and eCommerce platform, of how merchants allocate their variables in stores. This brilliant tactic is created to help match merchandise with customers’ interests and preferences in order to enhance the brand’s value. The elements of this strategy can be categorized into three main parts: what it’s being sold, where it’s being sold and when it’s being sold.
Assortment optimization refers to the problem of selecting a set of products to offer to a group of customers to maximize the revenue added by customer purchases according to their preferences. Assortment optimization is essential to a wide variety of application domains that include retail, online advertising, and social security since it reflects the unpredictability of supply and demand.
An optimized assortment brought out by proven analytics can enhance a brand’s product distinct and value. This exclusivity can help drive customers’ interest into the brand without competing in a price war or promotion strategies. Customers will automatically see the worth in spending their effort with the brand no matter what price it offers.
Assortment optimization covers distributing channels as well. The term optimized assortment mix refers to the act of optimizing assortment in both physical stores and online platforms. Determining the right assortment mix will give retailers a suggestion in space planning for both offline and online stores. It helps retailers make decisions for appropriate stocking and marketing strategies. When a product line witnesses a potentiality in selling, retailers can further consider developing and enabling more market space for it. Conversely, retailers may have to take product cancellation into account if that product line gains no profitability.
Market research helps business owners determine the target market domain and target customers by monitoring and analysing data of which brands offer the best in each category for retail rivals. Specifically, conducting market research gives retailers a better understanding of what and who to offer based on statistics and figures found from competitors. The research includes two relative elements to evaluate the situation: competitor analysis and customer analysis.
Make a visit on competitors’ websites, pages, blogs and evaluate their marketing approaches. Identify their offering products, target customers and average pricing then make a comparison with your own business. Determine how your products stand out from competitors’ to estimate the possibility your products hold in the market.
The purpose of this process is to grasp customer insights. Carry out surveys, questionnaires or short interviews on a group of potential customers about their purchase habits and preferences to assess the rationality of a business’s assortment. Then ask for the customers’ feedbacks of current product assortment to have proper modifying planning, but try to avoid biased opinions. On the Magento 2 platform, there are plenty of tools which help you collect priceless information from your actual buyers. Among those useful plugins, the Customer Attributes module works pretty smoothly, offering you a wide range of question forms to play with.
The data collected from the research initiate steps closer to an optimized assortment. These data, which hold a track of details about a specific product at different periods of time, can help seek for the potentiality of new products. They can correspond with the understanding of past and current tendency to examine if presenting a new product is worth an investment. Therefore, a clear and effective strategy to supervise and double check these data frequently is highly recommended.
The competitive data collected from the research should be taken specifically. Determine the categories that satisfy your set specific brand identity rather than trying a successful product line of a different brand without understanding the capability of the application.
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Ascertain the voids in the rivals’ assortment planning. The figures from the research enable retailers to discover what their competitors are lacking in (eg. brand identity, category, etc.). Retailers can take the chance and fill in those gaps by offering products with differentiating assortment that may satisfy customers’ specific demands. The offered products should follow the strategies of quality qualification, exclusivity, customization and localization (and so on) to win the game. With that in mind, retailers can create their own category and freely experiment their products to enhance the uniqueness in the competitive market.
The act of assortment planning helps ensure that assortment evolves over-time. Consuming behavior tends to witness a wild fluctuation in trends, and in order to be updated, retailers should always keep assortment data “fresh” and take the chance when possible.
The assortment planning process cannot be duplicated as it’s a specific trait portrayed differently among retailers. The market is being driven in this circumstance - it means products can be freely experimented without following an established set of rules.
However, make sure that inventory investment is worthwhile by conducting practical testing. In business, analytics always win over guts. Only by examining assortment data will retailers make better decisions. Start off the testing process with an investment in a small number of resources only to see how customers react to the sample products. If the reactions are relatively positive, invest more and reversely, if customers do not respond well enough, take immediate action on other experiments to keep resources intact.
The search function in web pages provides users an approach to find the content they’re looking for. The search functionality is optimized in the form of a search box consisting of a text field to insert a search term or a link with a search term included, and a button to trigger the search. Users can locate the desired information by adding keywords or phrases, rather than skimming and scanning through the whole website for contents.
When customers use the search function in a certain website, they are starting their customer journey with the initial step of researching for product data. By conducting search, customers ave implicitly expressed the desire and interest to give merchants some suggestions. Therefore, the internal website search is carefully operated to match the given hints.
On the one and, search feature helps navigate customers to the right page on the website to look for details about certain products, services, contacts and other relevant information. Potential customers also utilise internal website search to get support on how to unravel some business issues.
On the other hand, analytics gathered from this search tool can be a great resource to study about the tendency of visitors’ insights. By analysing these data, businesses can upgrade their website in terms of content quality, site structure reorganization, keyword search optimization and so on. Also, because the search statistics reveal customers’ demand in a certain information domain that the website hasn’t accessed, businesses can take this opportunity to update website content or attach reference links including blogs, case studies and other relevant sites to better promote.
In reality, search box is the key connection between businesses and customers on online platforms. The majority of customers use search box to find product information, indicating their potential intent of purchasing. In other words, the rising number of search function uses can massively result in the more chances of introducing products to prospective customers and increasing profits. Understanding this importance, businesses should always have a proper strategy to create an effective search box presenting the following critical features.
Drop-down suggestion list:
A search-suggest drop-down list (also known as drop-down menu) is a feature enabling users to insert a search keywords into a search box to get shortcuts leading to desired contents. Before completing the adding keywords manipulation, searchers will see a drop-down list with suggested completions that offer potential options.
This suggestion list is compiled from search history data gathered from other popular previous searches attempting to give searchers the closest keyword predictions. This feature not only quickens visitors’ searching and locating details process but also holds a capability of driving customers to check out different contents, not just the desired ones as well.
These days, customers’ perceptions are easily influenced by the standardized search functionality, with autocomplete feature holding a high expectation of optimizing search input. Autocomplete operates in the same way as the suggestion drop-down list, wit a typical difference.
When inserting a query into the search box, the drop-down list suggestions are based on data from search history, wile autocomplete suggestions are online assorted categories offered by the brand. Under proper implementation, this feature can help narrow customers’ category search down while motivating more product observations, auto-correcting misspellings and providing alternatives for unidentified items.
Stores can have a reference at the Ajax Search Extension to optimize the previously-mentioned features for your website search function.
Visiting eCommerce stores owning dozens of product categories and multitudes of product lines with various attributes stimulates an urgent need for a tool to optimize product searches. Layered navigation system was invented with indispensable features bringing a list of filters to provide great support for customers in finding the desire-matching items :
Online stores can now enjoy these outstanding features of Layered Navigation Ultimate on Magento 2 platform.
The creation of assortment planning strategy as undoubtedly opened a closer connection between businesses and their customers. While customers are experiencing shortcuts into product categories, businesses can take this advantage to gather data for further product and service experimentation. In other words, optimizing assortment enables space for a win-win situation in the market were both suppliers and consumers are happy with the trading.
Posted by Hant in Blog . July 18, 2019