E-Satisfaction and Social Interaction Create E-Loyalty

Retailers and service providers are moving online in an attempt to raise their financial performance. The online world has some different methods of marketing that help to retain customers. In the online world where there are low switching costs companies will need to spend a greater portion of their efforts on customer retention.  A study by Christodoulides and Michaelidou (2011) helps better understand what companies must do to create e-satisfaction and e-loyalty. 

Companies spend nearly double the amount of their budgets on new customer acquisition while spending half that amount retaining existing customers (Forrester Research, 2008). As a general rule, the cost of gaining new customers is about five times the cost of retaining current customers (Strauss, et. al. 2006).  The existing customers have long tail value and should receive greater emphasis in future strategic considerations. 

How e-companies retain their customers is an important consideration for boosting revenue.  Previous research has indicated that trust, customer service, website and technology, customization, switching barriers, e-satisfaction, and image are key components to successful customer retention. When companies can effectively carry a strong brand, matched with technology, and offer customizable products/services they are more likely to keep their customers coming back. 

Through the analysis of 797 the authors found that e-satisfaction was positively associated with e-loyalty. They also found that convenience, variety and social interaction help create e-satisfaction and slowly encourage e-loyalty. The more convenient the shopping experience the more likely e-satisfaction will rise. When shopping motives are strong and e-satisfaction is high there will likely be more loyalty to e-retailers.  E-satisfaction has some of the highest levels of association with e-loyalty.

Christodoulides, G. & Michaelidou, G. (2011). Shopping motives as antecedents of e-satisfaction and e-loyalty. The Journal of Marketing Management, 27 (1/2).

Forrester Research (2008). The state of retailing online: Marketing report Forrester Research. Inc. Cambridge, MA.

Strauss, J., El-Ansary, A., & Frost, R. (2006). E-marketing. Upper Saddle River, NJ.

Effectively Using Online Marketing Channels

Internet marketing is in an ever changing state of development with both successes and failures. At times it can be a cost effective approach to reach out to increasingly Internet savvy consumers but at other times the total online marketing mix may be incorrect leading to wasted resources.  Research by Li and Kannan (2014) delves into online channels, visits and purchases. Their study helps in understanding how channels work together to create effective practices.

Marketing channels range but often include direct URL, searches, referral sites, emails, and banner ads. It is also possible that customers may choose a display impression but never actually click upon it. Each channel has varying effectiveness in terms of its ability to encourage customers to make a purchase.  In other instances these channels may be used in combination along with newer mediums not yet incorporated into the mainstream. 

In any online marketing campaign there costs of effort and cognitive costs. Finding the necessary information to make the purchase has a cost factor (Shugan, 1980). If this information is difficult to find, doesn’t move to a purchase quickly, and is difficult to navigate customers may deem these costs as too high and simply move onto other sites without making a purchase.  The process of finding and purchasing should be smooth, simple, and use the least amount of effort.

There are also cognitive costs associated with the processing of information (Johnson, et. al., 2003). All processing of information takes considerable energy. Difficult to understand pages with irrelevant information raise cognitive costs. Marketing should encourage faster and simpler mental processing based upon the merits of the product and the audience. There are natural differences in the type of customers attracted. 

The authors found that it is necessary to estimate the effects of visiting and purchasing to find appropriate avenues of raising click to purchase rates. The channels often work together but those firms with strong brands can obtain as much traffic through organic searches as they can through paid searches. Paid searches constitute around 50% of online marketing expenditures but if removed customers switched to organic searches. Email and organic searches have a longer impact than click through ads and should have greater emphasis in a marketing campaign. Likewise, retargeting click through ads seemed to be less effective over time.

Johnson, E. et. al. (2003), Cognitive Lock-In and the Power Law of Practice. Journal of Marketing, 67 (April), 62–75.

Li, H. and Kannan, P. (2014). Attributing Conversions in a Multichannel Online Marketing Environment: An Empirical Model and a Field Experiment. Journal of Marketing Research, Vol. LI

Shugan, Steven M. (1980), “The Cost of Thinking,” Journal of Consumer Research, 7 (2), 99–111.

Bonding in Online Communities

Group attachment is an important aspect of retaining and maintaining customers. As groups begin to identify and interact with new members, they build additional identities with the service or product. Research by Yuquing Ren, et. al (2012), focuses on communication and the understanding of identity, bond, and community identity in online forums. Their study helps highlight how different types of attachment strengthen online interaction and customer retention. 

The far majority of business that seeks to build online communities fail to attract a critical mass of customers even when over a million dollars have been spent (Worthen, 2008).  The primary problem is that they have not been able to create and develop a level of attachment among members. Customers simply come and disappear after a few posts. 

Understanding that there is identity attachment, bond attachment and community attachment can help in fostering the right type of activities that create positive identity with the service. People must feel connected to other members of the group if they are to return to the site on a regular basis. 

Identity attachment can be seen as attachment to members who are similar in appearance or other difference that separates them. It is a primarily visual and surface type identity. Bond based attachments are focused more on connection to group members and seeing similarity in belief, interests or values. Group based attachment is focused on connecting to an entire community of online users. 

The researchers found that identity based attachment is much easier to foster in online communities. One generally must provide an identity, familiarity around products, and in and out-group type dynamics to encourage retention (i.e. you’re different because you use our service). Bond based and community based attachment requires the ability to have personal communications. This is much more akin to social networking than it is other types of online communities. 

Online communities act in the same manner as real life communities. Communication is the key component that allows people to feel connected to others and form an identify around particular aspects of interest. In the online world identity groups and community groups are easier to establish based upon the specific and genera interest in products or identity. Social bonding is more difficult and takes considerable amount of time and energy. It is difficult to determine precisely when and how long bond identity can be formed. However, the use of profiles and communication around topics can encourage this knowledge of other members.

Worthen, B. (July 16,2008). Why most online communities fail. Wall Street Journal.

Yuqing Ren, et. al. (2012). Building member attachment in online communities: applying theories of group identity and interpersonal bonds. MIS Quarterly, 36 (3).

Using Customer Profiles to Enhance Service and Product Marketing

Customers are the lifeblood of any business. Understanding the unique and rich data that comes from their core customer base helps in creating services that truly meet the needs of those customers as well as marketing the most relevant programs to the most interested parties. It creates a higher level of sales and satisfaction spurred by the interconnectivity of customers and the organization. The customer’s needs are better fulfilled with the offering of products and services they are actually interested in. Precisely how this is done is a process that can be learned and adapted.

With the advancement of the Internet and e-commerce the use of social research to understand customer behavior becomes possible. With the increase in customer data it is possible to create greater data mining and clustering of customer profiles to understand buying patterns and behaviors (Prasad & Malik, 2011). It is through the development of higher levels of data analysis that services can become more effective and beneficial. 

Let us look at an example. Analysis of a large database finds that customers who bought airplane tickets also purchased beach related products. Yet what if these customers were also found to purchase more outdoor gear and spent a greater amount of money on outdoor activities? It would be possible to build a customer profile based upon their exploratory and thrill seeking behavior. 

In order to understand unique social purchasing behaviors requires the categorization and analysis of profile customers. It requires a method of making meaning out of the historical data (i.e. purchases over time) being presented. Qian et. al. (2006 suggests the following:

• 1.)    Standardize profiles
• 2.)    Screen out uninteresting profiles
• 3.)    Using basic functions to categorize profiles
• 4.)    Apply algorithms to the categorizations
• 5.)    Identify unique profiles for further analysis

Once the profiles are standardized it is possible to categorize their behavior into clusters. These clusters are used for additional analysis and the determining of patterned behavior. That patterned behavior indicates that there are latent psychological functioning occurring and it would be beneficial to use multiple analysis methods to better highlight their behavioral thought processes. 

This process is fairly accurate and can lead to better marketing techniques based upon profile attributes and responses to previous marketing (i.e. previous purchases).  One simply needs to draw connections between the different sets of data and tests that were conducted over time. A study by Leung (2009) found that out of 1,500 profiles analyzed that 91.73% of customer profiles were segmented correctly. 

High levels of accuracy and a process for separating and analyzing consumer behavior is a benefit that organizations should not ignore. The use of more pin pointed marketing techniques further encourages efficient use of company resources by ensuring that products are actually of interest to the customer. Social research techniques can help identifying latent psychological functions that further enhance organizational profits.

Leung, C. (2009). An inductive learning approach to market segmentation based upon customer profile attributes. Asian Journal of Marketing, 3 (3). 

Prasad, P. & Malik, L. (2011). Generating customer profiles for retail stores using clustering techniques. International Journal on Computer Science & Engineering, 3 (6). 

Qian, Z. et. al. (2006). Churn detection via customer profile modeling. International Journal of Production Research, 44 (14).

Selling Products through Developing Online Communities and Lifestyles

Organizations that move online often find themselves at a loss in trying to distinguish themselves and create repeat customers in a virtual world where the possibilities and competition are endless. Research helps to solidify a concept called online identity and bonding that can help companies create communities of interconnected customers. When such communities are formed the interaction rate and login rates of the members increased providing more opportunities to sell products and services.

Online communities are collections of people with complementary interests who communicate through an online medium (Preece, 2000). As such the people within a community create bonds with each other, interact, and have an impact on each other’s lives. Businesses are constantly seeking ways to develop a customer’s identity with their products and brands. One of the ways they can do this is through developing online communities that take on a life of their own beyond specific offerings.

Generally, these communities exist and succeed because members become attached to each other. When this attachment is strong they participate more and are retained in the group longer. Think of Facebook and how through family and friends we seem to be drawn over and over to check each other’s lives and statuses. The process of building a community around the lifestyles associated with certain product groups can maintain life-long loyalty.

Let us look at an example; if you are an outdoor enthusiast there are certain products that you will naturally take an interest with. These products might include canoes, outdoor camping equipment, guns, outdoor recreational vehicles, certain types of clothing and much more. Those items will have special interest and meaning for the members of the group as they communicate with each other and share experiences. 

Online communities are all about those experiences. Attachments are created when people develop a sense of group identity where both purpose and character are developed (Hogg and Turner, 1985). Obviously, you can’t just sell products and expect to have loyalty. Such groups could develop around themes, articles, lifestyles, how to advice, trip reviews and much more. You are selling the lifestyle in order to sell your products. 

Companies that offer different varieties and forms of these products could work together in a community hub. They can develop a social group online and provide relative content and interaction that furthers interest in the lifestyle. The sales pitch and information about products could be embedded into the content provided as well as the site itself. To do this well would required to focus on the development of relationships and bond among members (Festinger, et. al., 1950) above and beyond the products. 

A study conducted by Yuquing et. al. (2012) helps to show which factors help create these online communities. The researchers used a site called MovieLens.org to test their independent and dependent variables. The site offered movie ratings and recommendations. The site also offered a group profile page, group communication stats, individual profile pages, and methods of communicating. The study used a control group and a testing group that manipulated the variables. 

Results:

-Participants reported that the profile page and the movie group features were most important while the communication feature was least useful. 

-Support for the positive effects of identity-based features and weaker support for bond-based features.

-When compared to the control condition participants in the experimental condition increased their attachment to the movie group but not to the site as a whole. 

-Participants with access to profile pages visited the pages more often. 

-Exposure to group activities increased frequency in identity conditions but not in the bond conditions. 

-Those in the identity condition with access to both group profiles and repeated exposure to their group visited the site with twice the frequency.

Analysis and Business Application: 

Frequency of visits and sales are associated concepts. As people continually return back to their groups and profiles they will naturally be more exposed to advertisements and influences. The research helps highlight that having a profile and group outlets are important. One provided self-identity while the other provided a group to interact with. The research also supports a concept that through self-identity features we create a level of group identity. The research doesn’t indicate how self-identity and group identity influence each other. People with profile pages visited the site more often. When the profile page and repeated group exposure were available the frequency of visits doubled. This helps give some support to the concept that individuals create their own “personal space” with profiles and will interact with groups of “like mind” to create a sense of community. Yet all of this is through self-identity versus bonding which means that online groups are collections of people with pre-existing similar interests. In other words, one must be interested in your site and products already to become productive and connected individual with others of shared interest.

Festinger, L., Schacter, S., and Back, K. (1950). Social Pressures in Informal Groups: A Study of Human Factors in Housing, Palo Alto, CA: Stanford University Press.

Hogg, M. and Turner, J.(1985). Interpersonal Attraction, Social Identification and Psychological Group Formation. European Journal of Social Psychology, 15 (1).

Preece, J. (2000). Online Communities: Designing Usability, Supporting Sociability, Chichester, England: Wiley.

Yuquing, R., et. al. (2012). Building member attachment in online communities: applying theories of group identity and interpersonal bonds. MIS Quarterly, 36 (3).