Shazeeye's Blog Thoughts on User Experience, Technology and Business

29Jan/120

Value Proposition and Positioning: IKEA Case Study

A key concept in marketing is identifying value of a company (value proposition) and communicating (positioning) it to target customers. To define these concepts we answer the 4 key questions below for IKEA.

What does IKEA do well? IKEA’s cost leadership and unique Swedish designs provide its target customers (young buyers) excellent value.

What are the trends in the industry? Americans love to keep furniture. Ikea tried to change these attitudes with an advertisement (lamp has no feelings). The trend is to update furniture based on lifestyle changes (single, married, student, starting a new family, etc). Providing interior design expertise is a critical part of this industry. Manufacturers and distributors are joining forces. Flexible furniture (example: bed plus sofa in one) and furniture that serves dual purposes add value (example: bed has storage too). Distinctions between rooms disappearing – kitchen and living room furniture (example: chairs) is interchangeable. Personalization of furniture is on the rise (color, upholstery, wood stains, etc) and so is experimentation with new materials (jute, etc).

What is the competition doing? The competition is using four (or a combination of these 4) strategies: cost leadership, design differentiation, catering to certain market segments (international, demographic segments-young and old, psychographic segments-improves self image, retail, office, etc) and enhancing the shopping experience (design consultants, in house restaurants, etc). Image on right shows cost leadership and design differentiation for a few competitors.

What does the customer want? Customers want great designs in unique styles to match their lifestyle for low prices.  They would like an expert to do the interiors of their home for free. They don’t want to burden themselves with transporting furniture from store to home or having to assemble it. People are willing to spend more on furniture items such as a bed (indicated by the wide range in prices) or items that serve dual purposes (futon serves as a sofa plus a bed). It should be easy to maintain (odors, scratches, etc).

What is Ikea’s positioning strategy relative to its competitors?

Cost Leadership (30-50% lower than competitors): This global furniture retailer based in Sweden targets young furniture buyers who want style at low cost. Buyers trade off service for cost. Ikea designs its own low-cost modular ready-to-assemble furniture (big part of their cost leadership).  Customers do their own pickup and delivery or get it delivered for a fee.  Employees are trained to save electricity and managers always travel coach and take buses instead of taxis. Cost is so important that first a price point is established, and then the manufacturer, materials and design are chosen. Expensive wood is used only on top visible layers of the furniture. Suppliers are chosen from a pool of 1800 to maintain cost leadership.

Shopping Experience: Ikea owns the furniture buying experience. It displays every product it sells in room-like settings so customers don’t need a decorator to help them imagine how to put the pieces together. Ikea's in house Swedish restaurant is as popular as its furniture and provides respite to customers who walk through 25,000 sq m (average space of Ikea store). Customers move along a predetermined path through a maze of rooms. Ikea offers services aligned to its customers who are young but not wealthy, likely to have children but no nanny and because they work for a living and need to shop at odd hours they are open late and on weekends. They also offer furniture delivery services for a fee.

Swedish Designs (functional and simple): Ikea creates functional cookie-cutter Swedish designs (designs are part of their ‘matrix’). That one table only comes in 4 Scandinavian styles at 3 price points. Design is usually the last step (after choosing, the price point and manufacturer) in the process. Other than its staff of 10 designers it also depends on freelancers highlighting that design was to focus on simple yet functional styles.

4Jan/120

Two Consumer Behavior Models: Hierarchy of Effects and Elaboration Likelihood

Understanding consumer behavior, decision making and buying are critical aspects of any business. Consumer behavior models is just one of the many ways (real time observation and analyzing past data are some others) experts simplify this complex process. Let's look at two consumer behavior models: Hierarchy of Effects and Elaboration Likelihood Model.

Hierarchy of Effects: This suggests consumer buying behavior can be explained in phases. We need to influence and monitor these phases which range from first influencing the lower  level objectives such as awareness and understanding of the product to higher level objectives such as associating feelings with the product to encouraging purchase and regular use. This can be represented by a pyramid with fewer consumers  at the top than the bottom and each step has definite methods such as advertising or a sales promotion to encourage consumers to embrace the phase and move to the next in order to ultimately purchase the product. There are variations to this model as seen in the image below. Some examples: A fridge is utilitarian for most but Sub-Zero is hedonic. Toothpaste is mundane for most, but Tom’s could be considered utilitarian or self expressive. For some wealthy individuals, a Mercedes Benz may be mundane. A person could be a utilitarian when she starts to use the product and later be hedonic.

Elaboration Likelihood Model: Assumes consumers choose two routes before they decide which product to buy - the central or the peripheral route. The central route assumes customers are highly motivated, read a lot, weigh alternatives and make rational decisions. The peripheral route assumes buying is an emotional decision. Consumers can be persuaded  through cognitive and emotional responses and not through rationale or heuristics. For example, using the cartoon character Snoopy in Metlife's advertisements. Consumers tend to choose one over the other based on the type of product (big purchases could be peripheral decisions such as a car) and type of personality.


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30Nov/110

Micromarketing: Location data to better serve your customers – Part 2 of 2

Location data such as using a zip code to find out how much revenue a grocery store can make is critical in your decision to decide if you want to open the store at that location. This is just one example of the powerful potential of micromarketing. Read an earlier post to get the details. Let's look at some more examples of how micromarketing can be used in defining marketing campaigns and identifying sales trends.

Identifying Marketing Campaigns based on Market Potential: Market potential is the estimated maximum sales revenue of a product during a certain time period. MapInfo Professional visually depicts the market potential of households who spend more than $150 per week on groceries for each block group (group of adjacent zip codes) in Orange County. The software also gives details on which customer segment will most likely contribute to the sales at the grocery store. For details on customer segments based on PRIZM groups read the earlier post. We see that White-Collar Suburbia have the highest market potential (count* penetration) of 21.1% and hence will be the target of a marketing campaign. This group is well described and is very specific so a direct mail ad campaign is suitable. As this group is family centric and enjoys a healthy and busy (both parents work) lifestyle we can tailor the campaigns to emphasize healthy foods and easy to make dishes that brings the family together. We can also identify the market potential by block group so say if Block X has high market potential we will place a billboard in that area to target customers. We could also use coupons to entice the White-Collar Suburbia that live outside the trade area (area where customers that visit the store reside - usually a 5 minute radius for a grocery store) of the grocery store to visit the store.

Using Point of Sale Data (data collected at cash registers) to Identify Sales Trends: AC Nielsen collects a lot of data from grocery stores and can show sales trends based on customer locations (zip codes). As seen in the image below we see market share and sales over a year for 2 brands of cranberry drink - Ocean Spray and Coca Cola.

For Ocean Spray we see that within a retailer’s trade area the retailer’s total market share for Ocean Spray’s SS Cranberry Drink is 38.6%, a decrease of 4.3 points from last year. This means that the retailer sells 38.6% of this brand SS Cranberry drinks in this trade area. When we look at the Total Sales we see that the retailer’s sales is down 14% while the remaining market increased by  2.9%.  This means its sales decreased by 14% or people could be going to another retailer with a better marketing campaign (possibly a discount) for this drink in the trade area. The total sales were $700,000+ which is significant. Thus this drink could be a cash cow (based on BCG classification) for the retailer with the right marketing campaign. Plus, the sales for Ocean Spray or the remaining market increased by 2.9% though the overall trend for sales of ocean spray was slightly down by 3.6%.

For Coca Cola within a retailer’s trade area the retailer’s total market share for Coca Cola’s SS Cranberry drink is 23.6%, a decrease of 14.9 points from last year. This means that the retailer sells 23.6% of this brand drink in this trade area. When we look at the Total Sales we see that the retailer’s sales is down 62.3% while the remaining market decreased by  23.5%.  Thus this drink is a dog for the retailer and should be dropped as its market share is less than 35% and its total sales % change is less than 5%. Plus, overall sales were $1450  which is nearly insignificant (less than 1k is insignificant).

30Nov/110

Micromarketing: Location data to better serve your customers – Part 1 of 2

Location data such as using a zip code to find out how much revenue a grocery store can make is critical in your decision to decide if you want to open the store at that location. This is just one example of the powerful potential of micromarketing. Let's go through an example of using location data to open a grocery store in Orange County. We will be using SRC's Allocate to help analyze the location data and MapInfo Professional to map the data.

Mapping propensity and density to determine revenue potential of the store: As we see in the images below, we use SRC's Allocate to determine the revenue potential of  a grocery store in Orange County (OC). We choose the retail store option as the input variable and the dollar per store as the output using the software. Data is also available for furniture stores, sports stores, etc. After the variables are input a map is produced (below) which can be interpreted as follows. For Orange County, the average grocery expenditure per house hold per month (propensity) across a block group (a group of zip codes) where darker green shades indicate  higher expenditure for groceries per household per month is approximately $5800-$16900/month for the darkest or most expensive parts. The hashed region shows total dollars spent for groceries per square mile per month in Orange County (expenditure density). The darkest hashed regions indicate people in OC spend a total of $18,000,000 to $103,000,000 per month on groceries. This data helps you determine if the revenue potential is close to what you expect and can help compute your approximate profit given all the expenses you will incur. It also helps you compare revenue potential across different locations to help you determine the ideal/optimal location for you.

Choosing a Store Location by Mapping Competitors Location Data: Using the Yellow pages we identify the zip codes of the competitors. For this example - a grocery store - let's assume it's Trader Joe's and Whole Foods. We identified 19 Trader Joe's and 2 Whole Foods store in the OC area and mapped their trade areas (area from where customers visit the store - usually a 5 minute radius for a grocery store) using the software.  The blue areas represent the Trader Joe's and the red and fluorescent green represent Whole Foods. This is mapped on the propensity and density map from above using MapInfo Professional. With this information we choose a location (in yellow) that is far from competitors and has good propensity and density. You will also check for magnet stores, customer demographics and traffic (info in next paragraph) and ensure that the information provided by these parameters will help drive your store's growth. You can also compute the break even demand (average retail demand per square mile) as seen below to inform your decision.

Identifying magnet stores, traffic, customer demographics and trade areas for the new store location: The software helps to draw the trade area for the new store location (for this example a 5 minute radius as seen in black) and can identify the magnet stores or stores that will help pull traffic (for example, drug stores).  It computes traffic - 32,800 cars/day. It also helps define the type of people in the trade area. Types of people are defined by PRIZM clusters (for details check  PRIZM Clusters) and gives you demographics and characteristics of the population you are likely going to attract. According to the report this store will attract 54% of people belonging to the PRIZM cluster defined as White-collar Suburbia. This group can be described as "upscale, college-educated baby boomers living in suburban comfort in expensive new subdivisions". For more details on this segment visit Experian's description. Now that you have such a wealth of information on your customers you can tailor your marketing message as well as grocery needs to better suit them.


30Aug/110

Managing Disruptive Innovation

PARC or Palo Alto Research Center, a Xerox Company in Silicon Valley has contributed tremendously to commercial innovation through ethnography. I am a huge advocate of ethnography and PARC pioneered this process of studying human behavior and "hybridized" it with other social science and analytical methods to optimize it for business application - particularly for addressing new opportunities, customers and markets. PARC owns 2500 patents and have created products such as GroupFire (acquired by Google), Inxight (acquired by SAP) and Uppercase (acquired by Microsoft). You can see some of their presentations here. On August 18th I went for a presentation on Managing Disruptive Innovation by Tamara St. Claire, VP of Global Business Development and Head of Commercial Operations.

Tamara spoke about managing disruptive (vs. incremental) innovation, its risks, two case studies and lessons learned.  Incremental innovation happens in existing markets (left column in image on right) while disruptive innovation happens in new markets (right column) and is more challenging to manage. She mentioned three risks in disruptive innovation - technology, market and execution- emphasizing that markets and execution are the most challenging factors to overcome. A further breakdown of the risks are found in the image below. Lack of credibility/experience (includes C level stakeholders), lack of channel (sales/distribution network) and lack (actually the inability to filter through too much) of information are critical risk factors.

The best way to enter a market of disruptive innovation (with existing or new technology) is to start with a minimal viable product (MVP) introduced at the right time and a strong value chain. MVP is a product with a limited set of features that fits the user needs of a niche market. Once the product has gained an audience ideas to gain mass market with added features can be explored. Tamara gave an example of one of PARC's chip packaging technology which was introduced seven years ago but shelved due to bad timing. It was reworked seven years later by partnering with Sun Microsystems and Oracle due to their advances in chip technology. The value chain are a group of activities (see image below- extreme right) that help to bring the product to market. In existing markets best practices help define a path to market entry but in disruptive markets one has to be flexible and shift gears depending on learnings. It is also critical to partner with experts and consultants studying these new markets as well as visit trade shoes and conferences to learn as much as possible. Partnerships are forged to strengthen the chain and build credibility.

Case Study: Printed Electronics Services

PARC developed low cost disposable printed flexible electronic expertise and devices can be applied in health electronics, packaging and biomedicine. When DARPA (Defense Agency) contacted them to develop an early detection solution to prevent brain injury for soldiers they partnered with consultants and experts to expand their printed electronics services for defense applications. They soon realized they couldn't manufacture the films at the scale desired and thus decided to play a connector role (flexibilty to change is key) between materials and manufacturing.  They partnered with Polyera and 2 other manufacturers thus giving up positions in the value chain and concentrating on their strength (network orchestrator). The lessons are outlined in the image on the right where N=1 means that they relied on more than one consultant or expert to help traverse this new territory and in many cases related to disruptive innovation a group of experts help bring together a holistic viewpoint and a superior product. The other lessons were to be flexible to change course, focus on strengths in the value chain and partner in areas of weaknesses.

Case Study: Content-Centric Networking Protocol

PARC developed a communication protocol complementing existing IP infrastructure to reduce the cost of distributing video and other content in IP/TV networks. Content-Centric Networking uses a unique architecture that caches content closest to the users who request it most thus reducing network capital cost and operating expense.  To create this solution PARC collaborated with Van Jacobson, Chief Scientist at Cisco and an IP/TV expert and took it to open source for feedback. They tested this network with the government and early adopters and used feedback to improve the solution to get critical mass. The lessons here were to get the right commitment, gain critical mass and engage user feedback early.

Overall lessons are to use ethnography to understand how people are using your products and thus have a well defined MVP. Disruptive innovation is more about unique business models and integrating technology. As a company expands it is critical to have a portfolio of products ranging from core to next gen products and using a process to manage this innovation can be the difference between success and failure.

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