Design Thinking and Doing, A Field Guide for ...

21st DMI: Academic Design Management Conference Next Wave London, UK, 1-2 August, 2018

Design Thinking and Doing, A Field Guide for Independent Retailers Verena PAEPCKE-HJELTNESSA, Anne CECILb a

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Iowa State University’; ONO Made in the 191 Competing with the online retail market has become increasingly difficult for independent retailers. The number one significant differentiator in brick & mortar retail today is providing a fantastic in-store experience. Large-scale and highend retailers increasingly leverage Big Data to craft their shopping experience employing Wi-Fi, RFID technology, sensors, motion activated cameras, and heat maps. Even if independent retailers can access the technology, there is little chance they will have the capacity to implement and analyse the data. Moreover, Big Data removes the human element, the quantitative data provides mainly statistics, but it cannot interpret that data with insight. Design thinking methodologies are one answer for independent retailers to compete with the resources available to large corporations. Positioning design as a strategic resource in the day-to-day business operations, to enhance customer experiences before, during, and after store visits is the goal of this Design Thinking and Doing Field Guide for Independent Retailers. This guide provides a process to evaluate key elements of the shopping experience, to identify and implement practical and relevant ways to improve the merchant-customer relationship by creating meaningful experiences. This paper discusses the development and testing of the guide in academia and practice and its future applications Keywords: Design Thinking; Independent Retail; Big Data; Field Guide

Copyright © 2018. Copyright in each paper on this conference proceedings is the property of the author(s). Permission is granted to reproduce copies of these works for purposes relevant to the above conference, provided that the author(s), source and copyright notice are included on each copy. For other uses, including extended quotation, please contact the author(s).

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VERENA PAEPCKE-HJELTNESS and ANNE CECIL

Introduction: Alternative to Big Data One of the most significant paradigm shifts in Retail in the 21st Century will be the relationship between retailers and their customers. The advent of social media has changed the marketing funnel from a system of oneway communications to highly defined groups of customers into a system of two-way communication to a market of individuals. Big Data is playing an increasingly larger role in the communication system as big brick & mortars follow the e-commerce lead to collect and analyse vast amounts of data with predictive algorithms and machine learning (Turow, 2017). Big Data has been present in retailing since the implementation of computer based POS systems tracking inventory and sales early on and growing to include customer data, primarily through loyalty programs. More recent methods have included tracking customers through in store Wi-Fi, beacon technology, RFID technology, sensors, motion activated cameras, heat maps, etc. As noted by Bradlow, Gangwar, Kopalle, & Voleti (2017), the collection, integration and analysis of Omni-channel data may help retailers understand, track and map customer journeys across touchpoints, evaluate profit impact and better allocate marketing more effectively. They further note that retailers have a mixture of “good data”(recent data), “bad data” (old data), incomplete data (in-store and online data not linked), which often results in poor analysis (ibid). According to Turow (2017) in the not so distant future shoppers every move in-store and online will be monitored, evaluated and acted upon in real time through store representatives who might be provided with personal data (names, age, income, family status, photo, previous sites visited online, etc.) as the customer enters or coupons sent to the customer for use at check out. Even with an army of data scientists and analysts behind them, predictive algorithms often arrive at incorrect conclusions. For example, ads received on Google search typically reflect the demographic and specific search history, but the conclusions the algorithms draw are often wrong, which can be seen based on the ads Google presents. In addition the digital footprint has translated into print catalogues that are received via the postal service desired or not. In a world where the customer accepts and expects highly targeted communication, miscues in data analysis lead to companies not only wasting time and money communicating with the wrong end-user, but they are also bothering and in some cases offending consumers who have no interest in their products, services or brand. At a time where everyone has a voice, this has the potential to create a negative effect with public complaints and negative feedback in fact damaging the reputation of the brand. As a result, Bradlow et al. (2017) call for a more holistic approach in which the addition of theory can provide structure to investigate cause and effect, the drivers of outcomes, underlying factors creating new trends and false patterns. Because theory is continuously updated as trends and foundations change, managers can apply current context to the data analysis and adjust for inconsistencies with current practice.

Opportunity

Our defined Independent retailer core values are most often grounded in providing face-to-face, human customer interactions. Because they are local, they provide a sense of community. Therefore, their in-store experience is primed to meet customers’ social needs, however, they must still work to remain competitive. Grewal, Roggeveen, & Nordfält (2017) have noted in ‘The Future of Retailing’ that it is unclear if new technologies, a primary source of data, will affect all types of retailers and customers in the same way. Marr (2016) in Big Data For Small Business for Dummies, argues yes and no. He states the ten key big data collection tools are either platform or technology oriented. Relying on platforms like LinkedIn, Facebook and Twitter for data are dangerous. As we have recently seen with the Facebook scandal (Badshah, 2018), platforms will change what they collect and what type of data is available based on their own pressures, not to mention finding and collecting this data is time consuming and it may or may not be good data. Requiring a dollar and time investment technologies used to track such data as smartphone GPS, Wi-Fi signals and machine sensors, acquiring good Big Data is less accessible to the small scale, local independent retailer. Even the lower end technologies add a steep learning curve to the daily tasks of an independent retailer leaving these sources more trouble than they are worth. Transaction, financial and customer data acquired through the POS system and loyalty programs are the most likely way independents will collect and interact with good Big Data.

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Design Thinking & Doing, A Field Guide for Independent Retailers

The research team recognizes that the experience and knowledge of the retailer and the power of observation are two components missing in the current conversation surrounding Big Data. With a specific interest in small independent retailers who find taking care of every aspect of their business leaves little time to address the problems associated with collecting and analysing Big Data, we saw an opportunity to develop a seamless integration of Design Thinking methodologies into day-to day business practices. Thus, providing useful, meaningful tools that allow them to remain competitive in the 21st century retail model with a real alternative to Big Data. Retail success is based on creating an excellent user-focused experience throughout the shopping system. The user in this case is the customer and the product is the experience; applying design methodologies to facilitate structured conversations with stakeholders, but more importantly with the end-user. The 5-step process: project definition, exploration/synthesis, concept generation/prototyping, evaluation/refinement and launch/monitor grounded in immersive research and design ethnography can be practiced with adequate guidance, which is at the core of the development of the Design Thinking and Doing Field Guide for Independent Retailers. The word ‘doing’ was purposely added to the title to emphasise the action oriented aspect of the field guide for the non-design experienced audience. For this research we define the Independent retailer as follows: • • • • • • • •

Annual gross sales: $1 million-$1.5 million Number of Stores: 5 or less Geographic Reach: Stores within 200 miles of each other. Category: Specialty Store Format Locations: Downtown, Free Standing or Strip-Mall Mini-chains (considered local for the most part 3-5 stores with a 200 mile radius) Years in Business: 15+ Profile: Often not educated as retailers-were passionate about a category and turned it into a store. Often passed on through family.

Origin of Collaboration This research began with the idea of integrating Design Thinking methodologies into a retail based project for Design & Merchandising students. The collaboration between Merchandising, Product Design, and Design Thinking is a natural fit for retail investigation. Merchandising as a discipline exists to get product from concept to consumer, primarily through a retail outlet. Product Designers on the other side create product sold at retail. Design thinking methodologies are often used in product design as they help product designers understand and empathize with the end-user which leads to more insightful products (Kolko, 2011; Martin, 2009). Grounded in observation, the first iteration of our Field Guide used a variety of techniques designed to challenge the student to observe a particular location over a period of time, in response to an RFP (request for proposal) announced by a local London council that was looking for creative ways to revive retail at various points on the local high street. Overall the guide was well received and final projects reflected a deep understanding of opportunities based on immersive observation and affinitizing. Based on user input, the guide was revised for clarity of communication. It was next used over a 3-year period in a global classroom with Design & Merchandising and Marketing students from the USA and Writing for the Creative Economy students in Hong Kong. Students used the guide to act as agents on the ground for their international partners to provide specific information about an assigned shopping zone. Overall, the guide was effective, not only in the deep understanding of a shopping zone, but also in the communication of the observations and understandings to international partners. The methodologies used provided a structure for observation, analysis and conversation. The visual aspect of affinity diagrams was particularly useful to clarify communications, which prior to the guide had sometimes been difficult with ESL (English as a second language) partners. It also allowed the students to ‘see’ the zone, find and verify patterns, identify opportunities and detect potential or actual problems.

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Student success after institution of the guide, particularly as they acted as agents, revealed how design methodologies could really help a retailer gain deeper understanding about their customer, selling floor and customer communication. Driven by the repeated positive feedback the Independent Retailer Field Guide project was launched.

The Importance of In-Store Shopping Experiences According to Verhoef et al., in ‘Customer Experience Creation: Determinants, Dynamics and Management Strategies’ (cited by Grewal et al., 2017) customer experience is comprised of cognitive, affective, emotional, social and physical responses to a retailer created by in-store, retailer controlled factors, as well as external, non-retailer controlled factors. Shopping habits are driven by needs, wants and impulse. As such a driving aspect of people shopping at a brick and mortar instead of Online is to have a great experience. One of the keys to success for retailers is to provide a positive exchange of goods or services, which is often initiated by the social interaction between the seller and the buyer. A positive customer experience can go a long way and is in some cases more about the interaction between people and the exchange of stories than about the purchase of items (Kepron, 2014). As a result in today’s world of social media and the increasing influence of the Internet-retailers, allowing people to buy everything, anytime, from anywhere, the in-store experience becomes more important. Feeling happy or satisfied after a shopping experience can determine people’s loyalty to a brand and/or retailer; these ‘retail places are becoming playgrounds that provide frameworks that support interaction between customers and brands’ (ibid, p.28). In ‘The Aisles Have Eyes’ Turow (2017) discusses how retailing is creating a hidden curriculum (according to Turow a term coined by Philip Jackson addressing unintended lessons learned) ‘reaching out to people with ideas about what’s good, bad, and ugly’ (ibid, p.16) creating experiences through different media such as packaging, through photos or scenes depicted in window displays inviting the targeted customer with like minded visuals, or clustering of stores in malls based on demographic and psychographic data. In addition the retail industry is fostering a new sense of willingness in the customers to share large amounts of personal data ‘teaching them what they have to give up in order to get along in the twenty-first century’ (ibid, p.13). Thus motivating a shopping experience often driven by loyalty, which becomes a crafted story beginning long before entering the physical store and ending long thereafter. Loyalty has been a key instrument for merchants to influence a lasting relationship with the customer providing benefits in return for consistent purchase behaviour. (Ibid) Connecting this understanding to Big Data, the statistical analysis of customer data and computer modelling algorithms seek to find patterns in transactions and shopping habits. The aim is to identify potential risks to businesses and also discover opportunities for experience creation that would be geared towards the shoppers needs and desires in an effort to make the overall shopping experience more enjoyable and relevant. Gathering digital information and offering opportunities for products or services in real time is becoming increasingly relevant, especially for the type of shoppers who seek product information while at the store standing in the aisle looking at the product. Thus, using predictive models to manage the customer relationship in real time is becoming more and more important (Kepron, 2014). But what if a retailer does not have the means, bandwidth, or desire to navigate Big Data?

Inquiry and Process Overview Developing alternative predictive models and crafting advanced customer experiences for the independent retail market is at the core of this research inquiry. Recapping what was previously discussed, in response to the Big Data or ‘Better Data’ (Bradlow et al., 2017) approach to collecting customer information in the retail industry as well as the drive to create better and more meaningful customer experiences, this research team set out to investigate alternative ways for independent retailers to gather and synthesize their own qualitative customer information. Based on the success of the above mentioned previous study where Design & Merchandising students were exposed to Design Thinking methodologies, the goal of this particular tool is to integrate Design Thinking methodologies into daily routines of independent retail professionals in order to provide them with means to

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create lasting in-store-experiences for their customers to be more competitive in the ever-growing Online and large and high-end retail market. The inquiry was driven by the following research questions: • • • • •

What is meaningful data to independent retailers to be competitive? What Design Thinking methods are most useful in leveraging their existing data? What Design Thinking methods provide maximized understanding of floor merchandising? How can these design thinking methods be seamlessly integrated in the day-to-day business practices? How can these methods facilitate competitive in-store-experiences?

Methodology and Overview of Design Process

The research undertaken was informed by the Double Diamond Design Process as defined by the U.K. Design Council (Hunter, 2015), further described by Don Norman (2013), and respectively broken down into four phases: Phase 1: Immersion into the context Phase 2: Interpretation of data Phase 3: Ideation and exploration of possible solutions Phase 4: Implementation and testing During the immersion phase the research team interviewed independent retailers, retail experts, and observed retail stores. Table 1 Methods used to collect data Aim (n=1) Immersion into the context

Research Technique Expert Interview

(n=9) Understanding store layouts (n=8) Understanding independent retailer

In-store observations

Collected Data General understanding of the independent retail market Comparison of store layouts

Interviews with owners and employees

Insights into day-to-day business practices

The collected data was analysed and synthesized. Design opportunities were identified and a set of recommendations was developed. Table 2 Methods used to analyse and synthesize data Aim Identifying patterns across independent retailers Comparing different store layouts

Research Technique Affinity Diagramming

Output Interview insights

Physical Model

Comparing display types Identifying customer behaviours

Artefact Model

Product placement Customer paths Common touch points Common touch points and displays Customer archetypes

Personas

The set of requirements informed the ideation process during which several variations of the field guide were developed. Two rounds of testing with independent retailers followed this phase.

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Table 3 Testing with independent retailers Activity (n=15) st Testing of 1 iteration field guide

Context Educational track at a trade show. Workshop set up: Lecture

(n=8) nd Testing of 2 iteration field guide

Session 1 Workshop set up: Hands on demonstrations and assigned homework Session 2 Workshop set up: Hands on demonstrations Sent out after both sessions.

(n=6) nd Testing of 2 iteration field guide

(n=10) Online Survey

Collected Data Observations and feedback of participants’ engagement and understanding of field guide. Observations and feedback of participants’ engagement and understanding of field guide. Observations and feedback of participants’ engagement and understanding of field guide. Feedback regarding gathering of data and implementation of field guide in daily routines.

In round one, the original field guide was presented in lecture format to a group of 15 participants in a retail educational setting at a trade show. In round two, the revised field guide was introduced to a group of 8 independent retailers during session 1 and revisited with 6 returning participants in session 2. Both rounds of testing informed revisions of the field guide for further implementation.

Development of the Field Guide and its Testing Immersion into Retail Context and Interpretation of Data

During the immersion phase several independent retail stores were observed and analysed. The focus was set on store layout and flow, point of sales for merchandising, and discovery of various touch points. Stores ranged from kitchen equipment, outdoors sports, candy and specialty chocolates, pet supplies, consignment, furniture, to equestrian supplies. Each layout was sketched out as physical models. Pictures were taken of the interior and analysed in form of artefact models (Beyer & Holtzblatt, 1997).

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Figure 1 Contextual inquiry and analysis of varying stores.

Interviews were conducted with storeowners, employees and a retail business expert. The goal was to uncover patterns of store layouts, set ups of merchandising and point of sales. The data was synthesized into a visual diagram depicting first round of opportunities for 2D and 3D store visualization and planning ‘kit’ addressing store layout, employees, and customers (figure 2). The initial goal was to develop a physical artefact based on the idea of a board game, which could be manipulated by the storeowner to explore his/her store layout. The storeowner would be able to test different layout scenarios to fit the varying seasonal merchandising. In addition a 2D guide would be developed allowing the storeowner to tap into his/her existing knowledge to craft customer experiences.

Figure 2

Opportunities to address user experiences

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Several requirements were solidified, which informed the ideation phase. The outcome would have to: • • • • • • • •

Be easy to understand with a low barrier for implementation Fit into the daily routines of independent retailers Address different levels of expertise in regard to design tools and methods Be adaptable to different needs and provide options Be non-linear in its approach and use Be encouraging not instructional Leverage the retailer’s existing knowledge Provide meaningful outputs

Addressing three of the research questions: ‘What is meaningful data to independent retailers to be competitive?’ ‘What Design Thinking methods are most useful in leveraging their existing data?’ and ‘What Design Thinking methods provide maximized understanding of floor merchandising?’ several design methods were explored and investigated for their fit to deliver meaningful information and hands-on guidance for the independent retailers. Based on the understanding of Big Data and what independent retailers are competing against the following design methods and tools were chosen to be tested. Table 4 Design methods & tools as they compare to Big Data technologies Design Method/Tool

“Expert Interview”

Personas

Journey Mapping

Touchpoints

Media Channels

Service Blueprint

Qualitative Data, Benefitting Independent Retailer Leveraging the existing knowledge of the retailer. Creating a set of customer profiles that can be used to design experiences. Understanding customer behaviour and movement through store. Leveraging existing instore touchpoints and exploring new opportunities Leveraging existing instore channels and exploring new opportunities Designing pre-, instore, and postcustomer experiences

Replacing Quantitative Big Data Technologies Demographic data from: loyalty programs, credit cards, IP addresses, survey data Demographic data from: loyalty programs, credit cards, IP addresses, survey data POS systems, geo-spatial location systems, beacons, floor sensors Integration and analysis of Omni-channel data, location based Loyalty programs, social media, IP addresses

Predictive analytics

Ideation and Testing of First Iteration Field Guide

The goal of this phase was to implement the previous findings while addressing the remaining research questions: ‘How can these design thinking methods be seamlessly integrated in the day-to-day business practices?’ and ‘How can these methods foster competitive in-store-experiences?’ The original idea of developing a 3D physical product based on the idea of a board game was dismissed after the first round of paper prototyping. Due to its cumbersomeness and mainly due to its size and the footprint it would

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have required when fully set up it didn’t deem useful for implementation at this point. Hence, the research team went on to explore variations for 2D deliverable, which in the end turned out to become the Design Thinking and Doing Field Guide for Independent Retailers. Figure 3 shows content explorations on the left and the first field guide iteration on the right side.

Figure 3 Field guide content exploration and first iteration

As previously discussed, the first iteration of the guide was tested with 15 participants as part of retail education track at a trade show and mainly presented as a lecture. Immediate feedback from the participants revealed that the information presented was too unfamiliar and therefore appeared to be daunting for the audience. The field guide did not connect the methods and process to the overall experience in a concrete easy to follow way. In addition to this round of testing the field guide was discussed with two additional independent retailers. In summary, the first iteration was a major failure. It did not meet expectations in terms of a seamless integration into the day-to-day business practices. Based on the provided feedback, the guide was revised for language, organizational structure and graphic cues. Existing literature on design methodologies, such as Kumar’s 101 Design Methods (2013), IDEO’s Human Centered Design Toolkit (2011) as well as the original Field Guide for the Experience Economy (Pine, Gilmore, 2015) were revisited. In addition design tools such as the IDEO Method Cards, Michalko’s Thinkpak brainstorming card deck (2013), and LUMA Institute’s Innovating for People planning cards and handbook (2012) were also analysed and re-evaluated for further investigation and understanding of how to better appropriate design thinking practices for non-designers.

Development of Second Iteration Field Guide

The feedback from the first round of testing was used to revise the guide for a second iteration. Main insights driving the revision were: • • •

• • • • •

Vocabulary needs to be less design-oriented and adapted to language that is used in retail. Language should be more concise and focused. The field guide needs to work within participants ‘comfort-zone’. Starting with sketching as the first exercise raises the barrier for entry. Starting with something participants know lowers the barrier and increases acceptance. Provide detailed examples of personas. Blank templates with little guidance increase barrier to adapting. Overall provide more guidance and examples for activities. Each activity should begin with a brief definition and desired focus. Integrate more specific retail information Facilitate synthesis for each activity for meaningful implementation

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Similar to the first iteration the revised version starts with an introduction to design thinking and how it relates to retail. Addressing one of the research questions the first activity: ‘Exploring Your Store’ revolves around tapping into the existing knowledge of the retailer in a way that was crafted as a soft lead in.

Figure 4 Tapping into the existing knowledge of the independent retailer.

The first task is geared towards thinking about their favourite store. The prompts ask for general aspects of that store as well as perceptions geared towards the five senses. The next step is to go through the same prompts with their own store in mind. The previous testing revealed that it would be easier to look at a different store first before analysing one’s own store. This exercise concludes by defining adjectives describing their own store and how they are currently manifested. Visuals were developed to easily capture peak times, slow times, and highvolume sales during those times. Most importantly, as was discovered during the first round of testing, each activity had to be synthesized in order to produce meaningful and actionable outputs. The testing of the first field guide revealed that creating customer archetypes requires a significant amount of guidance. Therefore, the second activity, which is geared towards customer observations, taps into the existing knowledge of the retailer in a more intuitive way. The guide provides hands on examples and a brief exercise. An additional set of customer cards provides more in-depth examples as well as an opportunity for the retailer to capture their own frequent customers in a visual way (figure 5).

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Figure 5 Persona-example for ‘Explorer’ and template.

Touchpoints are explored in the third activity and were broken down in three categories for simplicity and easy integration in the day-to-day practices. The exploration of touchpoints is mainly geared towards the actual in-store experience. As such there are touchpoints of person-to-person interaction (e.g. store employee with customer while checking out) and customers interacting with physical manifestations in the store, such as the fitting room. Although not a focus of this particular activity, touchpoints referring to media interactions were also introduced and picked up again later in the all-encompassing activity five. The fourth activity is geared towards a store mapping exercise with a focus on understanding areas that are more highly trafficked than others. Observing customer routes, touch-points, and lines of sight, facilitates visualization of areas that bring success and help identify areas that need improvement. These visualizations of customer journeys through the store can lead to insights on customer buying patterns, uncover overlap of popular foot traffic, and provide a better overall understanding of how customers experience the store layout.

Figure 6 Store-mapping instructions.

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The guide culminates in an activity to connect and create pre-, in-, and post-store visit experiences drawing from the methodology of a service blueprint (Polaine, Løvlie & Reason, 2013; Strickdorn, Schneider, Andrews, & Lawrence, 2011). The first iteration field guide of this activity was incredibly overwhelming for the participants leaving options for too many decisions to be made. The second iterations therefore reduced front stage and back stage lanes to: Experiences through touchpoints and logistics required to accomplish experience, both for pre-, in-, and post-store visit.

Figure 7 Crafting customer experiences, pre-, in-, post-store visit.

Testing of Second Iteration and Feedback

The revised guide was introduced in workshop format to a small group of eight independent retailers who represented six different businesses. This time the concepts and workbook exercises were presented, discussed and demonstrated in class. “Homework” was given to explore the two activities consisting of the customer cards and user journeys. The outcomes were reviewed during the second week with six of the returning participants, who represented four different businesses. Discussions included not only the data collected, but also the challenge of actually implementing the methodology in the day-to-day routines. All participants reported the ease of working the observation into their regular workday. All participants validated what they knew about their store, but also found at least one or two things they were not aware of. One participant applied the activities to a gift shop in a brewery that was not easily accessible to visitors. Based on the customer profile/user journey the participant identified a more accessible space and smaller footprint that would work better. A toy store had two participants at the workshop, after the exercise, one of them figured out a better resolution to merchandising around a central column. The other one identified a "play space for try and buy", which they had not considered before. Another participant works for the gift shop at a zoo and identified a better location and layout for the low-end items purchased by the child visitors. During the second session, the second set of methodologies was presented, discussed and again demonstrated in the session. Participants were sent on their way to perform these investigations and synthesize their findings on their own. During the reflection discussion participants confirmed the tool was useful and that it had gotten them thinking about problems they had and how to solve them, as well as uncovering problems they didn’t know they had. A brief anonymous follow up survey was sent out to inquire about the usefulness of the field guide in terms of seamless integration into the day-to-day business practices as well as actionable outputs. The majority of the responses, 80% confirmed the ease of use of the field guide. All of them confirmed that they discovered new

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insights about their store, which they were able to turn into positive outcomes, improving customer experiences. In addition, it was pointed out that the hands-on introduction during the workshop session was crucial in their understanding.

Conclusion, Self Assessment & Analysis

In conclusion, as presented by Grewal et al. (2017), using technology can enhance the customer’s shopping experience AND increase business profitability, however, there are a host of limitations with Big Data. As presented by Chauhan, Mahajan & Lohare (2017) in ‘The Role of Big Data in Retail Customer-Centric Marketing’, these include: • • •

There is no universally accepted definition, purpose or role for Big Data in terms of Retail Management. Analysis of Big Data does not always lead to meaningful conclusions and therefore should not drive strategy. Value cannot be captured in a systematic way, as there are no universally accepted theories or frameworks surrounding Big Data.

All referenced journal authors concur that Big Data can help retailers understand customer behaviour when using the correct mix of tools and analytic skills. However, Grewal et al. (2017) further state that data is best used when findings are combined. As such the Design Thinking & Doing Field Guide for Independent Retailers provides a framework that blends design tools and methods through visual analysis uncovering insights informing the creation of customer experiences. Confirming this thesis the research and team findings show that for our defined independent retailers, the application of Design Thinking methodologies allows the retailers to leverage their own experience and knowhow (inherent data) supporting the development of meaningful and actionable information for strategically planning improved pre-, in-, and post-store customer experiences.

Next Steps

Next steps of this research will be geared towards further development of the guide and supplemental materials as well as further testing in academic and professional settings. The development of additional visual support materials, such as a poster visualizing the connections of all activities as well as action cards to go along with the guide will be the first step. The guide will then be integrated in a course of an Online Retail Merchandising curriculum and further tested with independent retailers. The findings of the testing will inform the third iteration of the Design Thinking and Doing Field Guide for Independent Retailers. Acknowledgements: We would like to acknowledge the Design Thinking student research team at Iowa State University. Emma Axtell, Emily Krause, Anna Olinger, and Carly Luft were integral in the development of both iterations of the Design Thinking and Doing Field Guide for Independent Retailers.

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