In addition, consumers' willingness to purchase on the Internet may vary depending on the attributes that Internet retailers offer for online-shopping i. Drawing upon the previous literature, the authors propose that product classifications have a significant impact on consumers' preference for shopping on the Internet, and the importance they assign to Internet retailers' attributes. According to the Ernst and Young Global Online Retailing Report MacIntosh, , there is a discrepancy between e-tailers and customers regarding why customers visit a site.
The reason for the discrepancy is perhaps that the type of product purchased is influential in determining which attributes are more important in choosing a retailer to patronize. In the present study, the authors attempt to clarify why e-commerce is not growing as fast as expected and why consumers prefer to purchase certain products online and not others.
The findings of the study reported here may assist academic researchers in marketing, advertising, and communication to build paradigms related to e-commerce. It may also help Internet retailers understand which Internet retailer attributes are important to consumers for specific product types so that they can communicate to them with proper messages and convey the appropriate product-related information on their Web sites and in their advertising. Although it is often speculated that the type of product purchased will have a significant impact on Internet retail patronage, little published research exists investigating the impact of the type of product-purchase on Internet shopping preferences.
Several research studies acknowledge that consumers' buying behavior characteristics vary noticeably across product categories. Porter suggests that consumers may base their purchase decisions on product attributes such as brand image, reliability, styling, and availability of servicing. Porter explains that retailers control some of the attributes which consumers may want in the product. For instance, the reputation and image of a retailer may be reflected in the quality of the product or image of the brand. Recognizing that consumer buying characteristics vary by product type, Porter points out the shortcomings of classifying goods into only two categories: He argues that the factors such as unit price and purchase frequency do not necessarily distinguish buying behavior between the two product classes.
Although not investigated empirically, the Bloch and Richins classification of goods theory suggests that consumers' shopping efforts vary with respect to type of product. While Copeland identifies goods in separate categories such as convenience, shopping, and specialty goods, Aspinwall and Holton propose that products reflect shopping effort more appropriately if they are placed along a continuum. Klein examines the Internet's influence on information search and proposes a consumer information search model using the principles of information economics and a goods classification model based on search, experience, and credence paradigms.
She demonstrates how search goods can become experience goods by three routes. Similarly, using search, experience, and credence product classification along a continuum, Brucks, Zeithaml, and Naylor develop a typology of quality dimensions for durable goods. They draw their model from Nelson , who distinguishes between two categories of products, search and experience, and from Darby and Karni , who add a third product category to Nelson's classification called credence goods.
Nelson defines a search good as one whose qualities and suitability a consumer can determine by inspection prior to purchase of the brand. More specifically, a good is a search good when full information for dominant product attributes can be known prior to purchase, whereas an experience good is one whose qualities cannot be determined prior to purchase Klein, Nelson , classifies experience goods as experience durable low frequency of purchase goods and experience nondurable high frequency of purchase goods and tests for significant differences in the advertising sales ratios for search, and the two experience good classifications.
Nelson finds significant differences among the means of advertising sales ratio for the three classifications. Nelson defines an experience good as one whose qualities a consumer cannot determine prior to purchase. Based on Nelson's work , Kline provides two criteria for classifying a good as an experience good. Darby and Karni originated the definition of a credence good: Ford, Smith, and Swasy characterize credence goods as those which for average consumers are mostly taken on trust Asch, Credence qualities are primarily found in professional contexts, such as medical services and pension plans, because consumers do not usually have the knowledge to evaluate them Asch Drawing from the previously published research on product typology and using Nelson's definition of search goods, Kline's two-fold classifications of experience goods, and Darby and Karni's definition of credence, the authors suggest that type of product search, experience-1, experience-2, and credence will influence consumers' purchase preferences as well as the importance they attach to Internet shopping-related attributes.
More recently, Ford, Smith, and Swasy provided an operational definition of search, experience, and credence qualities in the context of a consumer's effort to verify advertising claims. Ford, Smith, and Swasy continued with the examination of differences in consumer skepticism for search, experience and credence advertising claims. They reported that consumers are more skeptical of experience attribute claims than search attribute claims and more skeptical of subjective claims than objective claims.
Based on the research findings about consumers' skepticism for search, experience and credence advertising claims, the authors of the present study speculate d that because of the differences in consumers' information needs for different product types, their preference for shopping online will vary across product categories.
Particularly, given that the credence products are the hardest to evaluate even after purchase or consumption, consumers' desire to shop online for credence products may be lower than that their desire to shop for search or experience products. Similarly, the consumer's need to test or try out the experience products such as clothing and perfume experience-1 or cellular phone and television experience-2 will be higher than the need to experience search products such as books and personal computers.
As a result, their desire to shop online for search products will be greater than for experience products. Based on Kline's classifications of two types of experience goods experience-1 and experience-2 , information search for experience-2 products is more costly and difficult than for experience-1 products. As mentioned earlier, experience-1 products necessitate direct experience compared to experience-2 products. Therefore, the authors speculate that consumers will be more likely to shop online for experience-1 products than experience-2 products.
Generally, the type of product is expected to influence consumers' preferences for shopping with an Internet retailer significantly. Consumers' willingness to shop from an Internet retailer for search products will be significantly greater than their willingness to shop for experience-1 products. Consumers' willingness to shop from an Internet retailer for experience-1 products will be significantly greater than their willingness to shop for, experience-2 products.
Consumers willingness to shop from an Internet retailer for experience-2 products will be significantly greater than their willingness to shop for credence products. The importance of attributes in general is well-established in retailing as well as non-retailing in the context of catalog shopping. Eastlick and Feinberg investigated consumers' functional and nonfunctional shopping motivations in the context of print-catalog shopping, using sporting goods as the moderate purchase frequency product and clothing as the high purchase frequency product.
They suggested perceived value, order services, and convenience as functional motives, and company responsiveness and reputation as nonfunctional motives influencing consumers' preference for catalog shopping. Consistent with the Bellenger and Korgaonkar classification of recreational shoppers, Westbrook and Black identified the most prominent motives of highly involved shoppers in the context of retail stores to be economic role enactment, choice optimization, negotiation, affiliation, and sensory stimulation.
In line with the previously published research in retailing, researchers have attempted to assess the importance of various e-tailer attributes, often with mixed and inconclusive results. For instance, Jarvenpaa and Todd suggested that the most important perceived benefit of Internet shopping was convenience, while poor customer service, poorly designed Websites, and perceived risk were cited by online shoppers as negative factors. Their findings have suggested that consumers' shopping experiences on the Internet were both enjoyable and frustrating.
Consumers acknowledged the savings of time and effort compared to traditional shopping, but were not satisfied with online customer service. Further, consumers perceived goods and services on the Internet to be intangible and involve risk.
Szymanski and Hise investigated the role of online convenience, merchandising product offerings and product information , site design, and transaction security on consumers' satisfaction online. They found that convenience, product information, site design, and transaction security had a statistically significant influence on satisfaction with online shopping. Keeney studied the positive and negative aspects of Internet shopping experiences, and concluded that different customers would have different priorities for Internet shopping.
Bakos asserted that the Internet lowers the search cost to acquire information about seller prices and product offerings, and reduces inefficiencies caused by the buyer's search cost. Phau and Poon found that consumers were more likely to purchase, via the Internet, products and services that have a low outlay, are frequently purchased, have intangible value proposition, and are relatively high on differentiation.
Vijayasarathy and Jones examined the factors that affected consumers' attitudes and intentions to shop using print and Internet catalogs. They found that consumers thought that differences between Internet and print catalog media had to do with differences in reliability, tangibility, and consumer risk. Further, they suggested that factors such as product value, pre-order information, post-selection information, shopping experience, and risk to consumers influenced attitudes and intentions to shop using print and Internet catalogs.
Consumers' online shopping behavior and its characteristics still remain a conceptual domain that demands attention. Vellido, Lisboa, and Meehan proposed a framework to characterize Internet users' opinions on Web vendors and on-line shopping. They confirmed that consumer risk perception is the main discriminator between Internet shoppers and Internet non-shoppers.
They further reported that variables such as age, household income, and Web-usage patterns do not predict Internet purchasing behavior. However, Donthu and Garcia foundd that Internet shoppers were older and earned higher income than Internet non-shoppers. Moreover, Li, Kuo and Russell found that education, convenience orientation, experience orientation, channel knowledge, perceived distribution utility, and perceived accessibility are strong predictors of online buying status such as frequent online buyer, occasional online buyer, or non-online buyer.
It was found that most online shoppers are young males who were professionals, At Kuala Lumpur, Malaysia, Volume: Advances in Global Business Research 3 . Global Business Research, 3 (1), 4 - 6 January , Kuala Lumpur, Malaysia, pp. “Online Shopping worth US$3 Billion”, Jaring Internet Magazine, site. 1. Introduction. Online shopping has been a growing phenomenon all over the The current issue and full text archive of this journal is available at . for clothing online within the past six months do so at sites operated by a Magazine, Vol.
Rowley articulated the challenges facing the Internet retailer and shopper. The challenges include locating shops on the Internet, time involved in comparison shopping, security related to financial transactions, the customer base and profile, the nature of the shopping experience, and legal or marketplace control or lack thereof. Rowley pointed out that the Internet has not yet accommodated to the cultural and social issues associated with shopping. What has not been investigated extensively is the role that product classification plays in determining the importance of the Internet retailers' attributes.
The research findings by Lynch, Kent and Srinivasan indicated that impact of Internet retailers' attributes such as trust, affect entertainment , and site quality vary across different product categories. The results of their study also indicated that site quality explains loyalty or purchase intentions for high-touch goods such as t-shirts experience products but not for low-touch goods such as CD players search products. Thus, drawing from the literature on consumers' motivations towards store and non-store attributes and their preference for type of products, the authors speculate that product categories will have a significant impact on the importance consumers attach to Internet retailers' attributes, Similarly, consumers' emphasis on Internet retailer attributes will significantly influence their preferences for purchasing online across different product categories.
The hypothesized importance of different Internet retailer's attributes and product categories is exhibited in Table 1. For search products, attributes such as convenience, home shopping, order services, and economic utility will be more important than the other Internet retailer attributes. The importance consumers assign to Internet retailer attribute will significantly influence their preference for purchasing online across different product categories. The data for the study was gathered in two stages. In the first stage, data was collected to select products from each of the four classes—search, experience-1, experience-2, and credence—for use in the subsequent study.
Thirty graduate students from a large urban university in the Southeastern United States participated in the first phase of the study. The average age of the students was in the mid-thirties. The sample consisted of an equal number of males and females, from clerical, supervisory, and technical professions. Each had used the Internet before on a regular basis. After each description they were asked to list four products that they believed represented each category.
The four descriptions are given below:. A total of 64 products were listed by the respondents under the search product category, 70 products were listed under the experience-1 category, 87 products were listed under the experience-2 category, and 69 products were listed under the credence product category. Based on the examination of the product list provided by the respondents, the authors selected the two most representative products for each product class see Table 2 to be used in the second stage of the study.
We also focused on those products that are more readily available on the Internet so as to make the second stage of the study more relevant to the respondents. In the second phase, the data for the study was collected in two major metropolitan areas with a population of 3. The respondents were contacted during different days of the week and different times of the day.
The survey was administered only to those who were at least 18 years of age and had used the Internet regularly in the past. In comparing our sample to the Census of the local area we found that our sample was skewed towards the more highly educated and higher income respondent, and to skilled as well as managerial types of occupations. This was expected as we surveyed only those who were regular users of the Internet. However, the sample profile is similar to the national profile of the Internet users as reflected in the last GVU survey.
Percentages do not add to per cent due to missing values. Sample demographic characteristics continued. The demographic profile of sample respondents of four product categories actual count. The survey instrument had four sections.
In section one, we asked each respondent to indicate his or her preference for purchasing from the Internet each of the eight products selected from stage one of the study. The subjects were given a list of 50 statements designed to capture 11 different dimensions of internet retailers. The items were chosen from an exhaustive search of the literature in the area of Internet retailing as well as direct marketing e. A separate set of respondents was asked for the same information but assuming they were purchasing products such as clothing and perfume experience A third group of respondents was asked for the same information but assuming they were purchasing products such as cellular phones and televisions experience The fourth group of respondents was asked for the same information assuming they were purchasing products such as vitamins and water purifiers credence.
The administration of the survey instruments was randomized to prevent a response bias. There were no statistically significant differences in the demographic profiles of the four groups of respondents. A total of valid surveys was obtained. The breakdown of the sample size in each product category is as follows: A first step in the analysis was aimed at ensuring that the survey instrument captured all the attributes of Internet retailer. Hence, Principal Component Analysis with Varimax rotation was performed on the fifty importance of Internet retailer attribute items to examine their discriminant and convergent validity.
The analysis produced a clean factor structure with items loading on the appropriate components Table 5. Ten dimensions were obtained with Eigenvalues greater than 1, and 66 percent of the cumulative variance was explained. Only seven items did not load on the underlying dimensions. These two items were retained where they loaded because they seemed to be relevant to the respondents' information search; therefore, they were suitable items to measure the Information Service component. Since the two items did not measure either component rigorously, they were eliminated.
Therefore, it was eliminated. A total of three items out of fifty were deleted. The rest of the items that loaded on the appropriate components produced ten dimensions with high Chronbach Alphas in the range of 0. Thus, our analysis confirmed the presence of 10 attributes labeled as follows: A scale for each attribute was created by summing up the responses to the items loading on the corresponding factor. The preference responses to the two products in each of the four categories were combined to measure the overall preference for purchasing products from each category on the Internet.
The reliability alphas of the four product preferences were in the range of 0. Get a head start in improving your customer engagement via community and CRM software. Here are the best guides to walk you through each aspect. Now is a great time to starting thinking about chatbots. The very first step to ensuring your customers engage with your brand is to ensure they can SEE that they can engage with your brand.
Olive Ave uses subtle but clear on-site messaging to alert customers to a variety of customer engagement tools, including:. See how they did it below. Mountain Crest Gardens is, in my professional opinion, light years ahead of most ecommerce brands in terms of customer engagement. They used a tool — Rivet Works — to collect not just customer reviews, but customer photos of their products being used. Many brands with philanthropic missions, like Shongolulu, encourage customers to become brand ambassadors —— sharing the message with the world.
Turn yourself and your employees into personalities. Most ecommerce brands optimize for long-tail, at least at first. Getting high ranking for short-tail keywords is hard. Bigger brands typically win here because of their Domain Authority, which takes into account:. On-site content to draw in customers in times other than a purchase point is becoming super important for LTV increase without large marketing spend. Optimize your site as it currently is, and get content ideas now from these comprehensive guides.
Jackson Galaxy uses video, clear CTAs, lots of copy and tons of reviews to turn their product pages into an SEO-optimized landing page. BlanksUSA uses campaign pages as landing pages in order to drive long-tail traffic to products easily grouped for a specific customer segment. Mobile experience need to be on par with desktop. Optimize your forms, create mobile-first designs, load pages quickly. Understand how your customers use mobile and optimize. Just use a pop-up like Solo Stove does to help the customer decide where to go next.
Mobile experience will be key in Mobile traffic has already overtaken desktop traffic, and we are seeing mobile sales approach desktop sales. Retailers with a mobile-first mentality will outperform those that treat mobile as a second priority. This mobile-first mentality applies to everything: And while many may still be able to do so in , it is likely that the cost is going to go way up. Social media advertising is a popular channel for ecommerce brands to use to run campaigns, drive traffic and close sales. Good social media advertising and marketing is about 3 things:. Building a culture around your brand will be the only way to compete and thrive in a marketplace that turns everything into a commodity driven by price and reviews.
Tommy John uses a gifting video along with a customer testimonial in this re-targeted Facebook Ad. Rollie is an Australian brand that has clearly just launched in the US. They are likely targeting me based on my geographic location and having visited their site before. Nike is using the multiple photo option ad aka, not a video and promoting customized items in the ads. Facebook prioritizes videos and videos help build way more trust then just a regular ad. Videos are so powerful and using Facebook Custom Engagement Audiences you can sequence potential customers who watch 10 seconds of one of your videos to another video.
Using Facebook Video Ads combined with Custom Engagement Audiences alone you can sequence potential customers all the way down a video funnel that goes from Awareness to Engagement and then to Conversion. CRO stands for conversion rate optimization, which you can only do through data-driven optimization and decision making.
Conversion rate optimization allows you to run tests to determine which various designs, language, etc. Look for little wins here and there and over the course of the year you will find that you have made it far more likely that a visitor to your website becomes a paying customer. Regularly get your customers on the phone. Ask why they choose you. Ask what problems drove them to you in the first place.
Ask how they view you compared to competitors. Their answers are literally what should go on your website to connect more deeply with your market and generate more sales. Every brand has to first test their way to success. And the third is to be sure to share your successes and failures with everybody internally. That way, you can be sure you have a staff with a knowledge base. Last year, conversion was 4.
This has given us an edge against other clothing brands. I have 30 BigCommerce sites up and the reason I keep coming back is because my development staff and design staff are familiar with the templates and the backend. The cost of entry and cost to scale have dramatically reduced over the years. And because the cost to entry is so low, more people have entered. And a lot of those people are starting and scaling in ecommerce —— again, because the technology to do so costs so little.
Suddenly, marketing to earn your fair share of the market is one of the most important factors to success. My advice for other business owners is this: Rather than tying up time with manual data entry and packaging, focus on things that help your business grow — like marketing, business development, etc. Let tools and integrations take care of the other elements of the business, and outsource work when you need it.
Honestly, InStockAlerts is worth its weight in gold. Suddenly, all my customers wanted to know when a product would be back in stock. Then, I have more sales with no additional time spent. We also use PriceWaiter on our product pages — which lets the buyer name a price. On the backend, we have loaded up all of our pricing rules into the PriceWaiter system. That app knows if we are willing to sell X items for Y dollars —— as long as the order value is above Z.
We use several different integrations with BigCommerce right now, but we like the social tools that make it easy to optimize things like email campaigns we send out through MailChimp. We also like that the social media tools for Pinterest, Facebook, and Instagram make it much easier to share our products. Leverage new technologies and services to make purchases as easy as possible. Never forget that there is tech out there to help you solve a variety of problems. Email marketing has long held the 1 position as the most profitable growth channel for online stores.
All in all, email marketing drives increased loyalty, repeat purchases, net new purchases and increased AOV, and it can do all of that without you having to actually send individual emails to individual customers. Automation is the real winner here — and email marketing is a test-bed of measurable aspects you can manipulate in order to drive growth behind the scenes. Dorco sent out a personal email from the CEO of the company to promote an organization called ShowerUp —— a mobile truck that goes around to homeless communities to provide hygiene options —— like shaving —— to the community.
It also includes a coupon code so that you can give and get discounted off. This is especially true with Care. They run a gifts. Kelty, a camping site, does this incredibly well. Each of their emails is themed, with an image to support the message. Yes, they showcase products.
But they also showcase content to help readers and customers nail down their next adventure. A strong network of influencers is a vital part of building a strong, sustainable ecommerce business. Natori promoted their line of sports bras through fitness influencer Sarah Dussault. But in this case, the product they were promoting was a line of sports bras, so a fitness influencer like Sarah was a good choice. Skullcandy works with YouTube influencers to offer honest reviews of the product.
Thoughts like that help to convey honest value and feedback to the audience. Hello Subscription is a blog dedicated to promoting and reviewing subscription boxes. The review included more than 20 images, and detailed descriptions of the contents of the subscription box, about which Tom also shared his honest opinions. Omni-channel may be an industry buzzword, but the need for it at the level of growing brands cannot be ignored.
The second trick is to scale each of those channels, and subsequently the brand, effectively — maintaining exceptional inventory, branding and customer experience across the board. This also means that ecommerce brands need to focus more attention on how new tools and new customer behavior will interact. Omni-channel sales require businesses to rethink how goods and services will reach consumers or at least attract consumer attention.
Omni-channel management is process and strategy by which brands manage their inventory, branding and customer experience across a variety of channels. Gain control of your distribution channels, addressing sales tax liability and expand into international marketplaces. Today, they use the marketplace to sell returned items for a profit. When we get an eBay order, it still comes through as a normal order in BigCommerce, and that was very attractive to us.
BeachRC sells on eBay, Amazon, their webstore and brick-and-mortar. I would have never gone out to put products on Amazon on my own.