360PI: A WORLD OF OPPORTUNITY · Periscope.” The news came as something of a surprise: Although Vienna-based Lixto was one of Europe’s most highly-regarded pricing intelligence

360PI: A WORLD OF OPPORTUNITY Professor Robin Ritchie prepared this case for use in the Network of International Business Schools Worldwide Case Competition. The author does not intend to illustrate either effective or ineffective handling of a managerial situation. Certain names, data, and other identifying or proprietary information may have been disguised to protect confidentiality. Copyright law prohibits reproduction, storage or transmittal of this document without the written permission of the author. Reproduction of this material is not covered under authorization by any reproduction rights organization. Copyright © 2015, Robin Ritchie Version: 2015-02-17 Alexander Rink stared at the whiteboard on his office wall. On it, he had sketched out a table summarizing key data on various international markets. Clearly, there was enormous opportunity in expanding beyond North America, yet it was far from obvious what the company’s next move should be. Was now the right time to establish a more global footprint? If so, should it be aggressive or measured? Which countries or regions made the most sense? And, interwoven with all these questions: What types of customers should be targeted, and how could they be convinced to sign on? It was August 2013. Rink was CEO of 360pi (pronounced “three-sixty P. I.”), one of a handful of companies around the world that specialized in providing price intelligence to retailers. A serial entrepreneur with two decades of strategic and operational experience, Rink was a passionate believer in technology disruption and the opportunities it offered. Prior to assuming his current position, he had co-founded and run two internet startups for over 15 years, including one whose customer and user base spanned the world. Before that, he had served as a consultant with Bain & Company, earned an MBA from INSEAD, worked in automotive manufacturing in Portugal, and traveled extensively in Europe and Latin and South America. The son of immigrant parents, he was also fluent in four languages. As Rink was mulling his options, Jenn Markey, Vice-President of Marketing appeared in the doorway. “Did you hear the latest?” she asked. “McKinsey just bought Lixto. They’re planning on folding them into Periscope.” The news came as something of a surprise: Although Vienna-based Lixto was one of Europe’s most highly-regarded pricing intelligence specialists, they had virtually no presence in North America, and 360pi had not previously regarded them as a serious competitive threat. But with McKinsey operating from over 100 offices worldwide, the march toward globalization in the pricing intelligence industry seemed to be moving ahead in earnest. COMPANY Based in Ottawa, Ontario—capital city of Canada and a hub of the country’s high-technology sector—360pi was the developer and operator of a leading-edge proprietary software platform that mined publicly available retail data from the internet to provide customers with insight into their competitors’ prices and product mix (see Exhibit 1). The business model was one of “software-as-a-service” (SaaS), which saw

Page 2 360PI: A WORLD OF OPPORTUNITY 360pi host the platform on its servers and license it to customers on a subscription basis. Customers included all manner of retailers, from online-only merchants (so-called “etailers”) to omnichannel retailers to bricks-and-mortar stores, as well as a selection of manufacturers that wanted to know how their products—and those of leading competitors—were being priced at the retail level. In its original incarnation in 2008, the company’s focus had been on the consumer market. Then known as Gazaro, it had operated a website that gave advice on the best time to buy a wide range of products. Shoppers could visit the site to obtain information on pricing trends for particular products. In addition, product offers from merchants were assigned a “deal score” between 0 and 10 to indicate their attractiveness. Subsequent to Rink coming on board as CEO in mid-2010 (see Exhibit 2), the company performed a strategic assessment and determined there was greater opportunity in the business-to-business (B2B) market. Shortly thereafter, it began marketing a repackaged and enhanced version of its pricing software to retailers across North America. This proved both popular and lucrative, and led to significant growth in revenues and employees. By 2012, the company had shifted its focus entirely to B2B with the aim of becoming the leading provider of pricing intelligence for the world’s largest retailers. This was accompanied by a relaunch of the firm under a new name: 360pi, chosen because it suggested the company’s focus (“price intelligence”) and its software’s ability to extract data from all available sources. The shift to B2B was a rapid success, with several major customers signing on in short order. These positive developments did not escape the attention of the venture capital community. In 2012, 360pi attracted investment financing from the MaRS Investment Accelerator Fund, the Ontario Centres of Excellence, and a group of angel investors.1 In mid-2013, the company secured an additional $4.25 million from Texas-based Silverton Partners to hire more employees and scale the business to meet increasing demand for its solutions. By early 2014, it expected to have an employee count of over 30—consisting mainly of highly educated developers and analysts—and a customer base whose annual sales totaled more than $US100 billion. 360pi’s impressive growth mirrored a number of other, previous success stories within the Ottawa high-tech sector. Companies such as Mitel (internet telephony and enterprise collaboration solutions), and Shopify (integrated e-commerce and retail point-of-sale systems), had started in the city and evolved into world leaders in their respective sectors. Other firms had risen to prominence and later been acquired by larger entities. This list included business intelligence software leader Cognos (IBM), computer networking firm Newbridge Networks (Alcatel-Lucent), electronic form software firm JetForm (Adobe), and QNX Systems (Blackberry Inc.), a developer of operating systems used in mobile devices and in-vehicle entertainment systems. THE PRICING CHALLENGE Retailers faced two main challenges when it came to pricing: Price transparency and consumer price sensitivity. With the rise of e-commerce and the ubiquity of internet-enabled mobile devices, prices for the majority of goods and services were readily available to consumers from anywhere at any time. The existence of websites and applications (i.e., “apps”) that displayed prices from various retailers for identical and similar products made price comparison especially easy. Coupled with the fact that price was a single number that was directly comparable across all goods, this made it a particularly salient purchase 1 All currency amounts are shown in U.S. dollars unless otherwise noted.

360PI: INTERNATIONAL EXPANSION Page 3 criterion for consumers and heightened their price sensitivity. To achieve higher margins and increased sales, retailers—regardless of their online or offline presence—needed to be extremely savvy in the way they managed prices. For consumers, comparing prices was a relatively straightforward exercise. An individual considering a specific TV model, for instance, could compare prices by visiting the websites of leading retailers, or by checking a price comparison site, at the time they were ready to purchase. For businesses, the task was more complex. A category manager for a retailer of consumer electronics needed to know prices for all of the audio/video products they oversaw, across a broad range of online and offline competitors, in a dynamic environment that was characterized by frequent price changes. Moreover, they had to compile these data, benchmark against their own prices, and use this information to make decisions about how—or whether—to adjust their company’s pricing strategy. This not only demanded a significant amount of effort, the amount of data involved made the task increasingly challenging. Dynamic Pricing In contrast to the pre-internet era, many retailers—particularly those with significant e-commerce operations such as Amazon—frequently adjusted prices for their products and services on a daily basis or even more often based on market demand, competitor pricing, and other factors. This practice, known as “dynamic pricing” enabled companies to find a balance between the pressure to stay price competitive and the need to maintain margins. While it had long been the norm in such industries as hospitality, travel, and entertainment, dynamic pricing was becoming increasingly common in retail thanks to the rise of online merchants and the ease with which prices could be adjusted at a moment’s notice—usually with the help of a software algorithm. The level of price dynamism varied considerably across retailers, with some merchants, such as Apple and Staples, adjusting prices only rarely. Walmart was the middle of the range, changing prices on 6 to 8 per cent of its assortment on any given day. Leading the way was Amazon, which altered prices on 15 to 20 per cent of its product assortment at least once daily. This percentage typically doubled during peak shopping periods such as back-to-school and the month leading up to Christmas. A number of factors influenced the pattern of price fluctuations observed for a given product or category. Product life cycle stage was one consideration; mature categories with well-established floor and ceiling prices tended to experience fewer price changes, or none at all. Price level was another factor: Items in the $10s typically fluctuated by pennies, with frequent adjustments; items in the $100s fluctuated by dollars; and items in the $1,000s moved by hundreds but price changes did not occur as often. Finally, shopper behavior played an important role. For instance, video games experienced more frequent price changes in the evening than during the day because this was when most purchases in the category occurred. Retailers also varied considerably in the way they scheduled price changes. For example, warehouse giant Costco made most of its price changes on Saturdays and Sundays, while Target favored Tuesdays and Saturdays. Amazon’s changes were evenly dispersed throughout the week. Although the pattern observed for a particular retailer tended to be relatively stable, changes were occasionally observed when retailers updated their e-commerce strategies. Adjusting prices in response to competitors did not necessarily mean price matching. For instance, Amazon, the largest e-commerce retailer, usually responded to competitor price increases by raising its own prices, but by a lesser amount. Likewise, other retailers had their own systems and decision rules to

Page 4 360PI: A WORLD OF OPPORTUNITY determine when and how to respond to competitors’ price changes. Indeed, maintaining profitability often meant resisting the temptation to engage in knee-jerk competitive responses, and instead making adjustments that were only as large and as frequent as necessary to trigger or retain the sale. For this reason, the use of dynamic pricing did not, in and of itself, correlate with e-commerce success, either in sales or profits. Sears, for instance, was one of the most price-dynamic retailers, yet the company accounted for less than $5 billion in online sales in 2013—compared to Amazon’s more than $67 billion—and had posted quarterly losses on and off for nearly a decade. Business outcomes depended on effective use of the technique, underpinned by good data and sound decision-making, as well as other factors such as brand name, customer service, and delivery options. There were also geographic considerations, with products occasionally offered more cheaply in some markets because of lower transportation costs, local supply gluts, or the existence of a significant regional competitor. In addition to monitoring competitors and adjusting prices in response to market conditions, a number of retailers and manufacturers had also begun to adopt a complementary strategy—personalized pricing and promotions to consumers. The intent of this “differential pricing” approach was twofold: first, it made it possible to change prices in a way that could not be detected by competitors. And second, it gave companies flexibility to offer different prices to different customers, based on what was known about their price sensitivity, loyalty to the store, and receptiveness to various types of deals. While the best-known user of this technique had been Amazon—a move that led to considerable consumer backlash in the earlier days of e-commerce2—it was employed by many retailers across a broad range of sectors, including U.S. grocery giants Safeway and Kroger.3 THE PRICE INTELLIGENCE INDUSTRY The business of providing companies with price intelligence was sizeable and fast-growing. Since consumers could easily conduct searches online, and potentially buy from a different store if they found a lower price, retailers were eager to know what competitors were offering and at what price. With so many competitors, thousands of products, and prices changing every day—even intra-day—merchants needed help to stay on top of collecting and deriving insights from pricing information. As with other instances of “big data,” the challenge had transitioned from one of insufficient information about competitors’ prices to the reverse: By 2013, the amount of readily available price information was overwhelming. Price intelligence software offered an appealing solution, since it not only gathered massive volumes of price data, it helped make the information manageable and actionable. Customers could download reports about their competitors’ prices, product mix, and inventory levels, gathered in real time, and presented in a way that supported management decision-making. They would also get insights into competitive dynamics, such as who tended to follow whom when price changes occurred. This not only helped them choose an optimal baseline price for each product, it also gave them the ability to respond to changing prices. The goal was to increase both revenue and margins, though retailers generally prioritized one or the other.

2 Ramasastry, Anita, “Web sites change prices based on customers' habits,” June 24, 2005. Accessed January 1, 2015 at http://edition.cnn.com/2005/LAW/06/24/ramasastry.website.prices/ 3 Clifford, Stephanie, “Shopper Alert: Price May Drop For You Alone.” New York Times. August 10, 2012, p. A1. Accessed January 1, 2015 at http://www.nytimes.com/2012/08/10/business/supermarkets-try-customizing-prices-for-shoppers.html

http://edition.cnn.com/2005/LAW/06/24/ramasastry.website.prices/

http://www.nytimes.com/2012/08/10/business/supermarkets-try-customizing-prices-for-shoppers.html

http://www.nytimes.com/2012/08/10/business/supermarkets-try-customizing-prices-for-shoppers.html

360PI: INTERNATIONAL EXPANSION Page 5 360pi Value Proposition 360pi’s platform provided access to online retail price information for exact-match and similar products in a timely, easy-to-digest, and cost-effective manner. The software not only stored and analyzed billions of historical retail price points; each day, millions more were extracted from e-commerce websites and added to the database. Customers could request data on hundreds of thousands of products across an unlimited number of competitors, and receive reports and other decision-making tools via 360pi’s web portal, as an application programming interface (API) that allowed customers to view and work with data using their own custom app, on mobile devices, or even in spreadsheet applications such as Microsoft Excel (see Exhibit 3). 360pi’s software was also capable of tracking pricing data for similar items regardless of brand. This was especially important for two types of merchants: those whose business consisted largely of commodity or branded products that might be uniquely identified for each retailer, such as hardware stores, and those who either sold and/or competed extensively with private label brands. Customers had the ability to enter numerous unique attributes at the SKU level—in the case of screws, for example: length, metal composition and the number of screws in a box. Tracking similar products helped ensure that retailers were aware of other merchants selling a similar item for less. The company’s product suite included:

• 360price, which compared online prices of identical products across retailers over time;

• 360comparables, which compared online prices of similar products including private brands across retailers over time;

• 360assortment, which provided insight into different retailers’ online category and product mixes;

• 360live, which delivered real-time online retail pricing for specific products via any web-enabled interface (typically used by store associates to validate shopper price-match claims), and;

• 360insights, which provided at-a-glance visualizations of relative retailer competitiveness by category at specific points in time, as well as over time.

The 360pi leadership team believed that success depended on product innovation, a good understanding of customer needs, and an ability to adapt to rapid technological change. The software solutions needed to effectively track online price competitiveness were a moving target: improvements in crawler blocking technology made it increasingly difficult to extract online data without significant and sustained investment to respond to these advances. As well, competitive pressure had increased, with new entrants being attracted by the strong demand for price intelligence services, the dramatic increase in e-commerce penetration, and the ever-enticing lure of large enterprise retailers (notably Home Depot and Walmart) looking for technology firms to acquire. For this reason, 360pi invested heavily in its both its software development and customer service teams. Distribution and Sales 360pi had a dedicated business development team that worked out of the Ottawa head office. Most new customers came via word-of-mouth referrals, contacts made at trade shows, or inbound calls in response to media coverage. In addition, 360pi staff would occasionally travel to specific cities to deliver presentations to high-value prospects or service calls to existing customers. During these meetings, they would provide

Page 6 360PI: A WORLD OF OPPORTUNITY updates on new features and capabilities of the 360pi platform, and demonstrate ways to extract maximum value from the pricing data being collected. 360pi estimated the total annual cost of an individual salesperson at between $100,000 and $250,000, depending on employee performance and travel costs. While it had built most of its business through direct sales, 360pi was not averse to partnering with complementary vendors in cases where this made sense. For example, the company had signed an agreement with IBM to embed its price intelligence software in that company’s omnichannel pricing engine. For IBM, the agreement gave them access to industry-leading technology. For 360pi, the benefit was access to a vastly expanded base of customers, most of whom had a broader relationship with IBM. CUSTOMERS 360pi’s customer base consisted of a mix of large omnichannel retailers in electronics, mass merchandise, sporting goods, home renovation, and specialty pure-plays (i.e., retailers focused on single product categories). Practically speaking, there were no restrictions on what products and prices could be tracked by the company’s software so long as pricing information could be found online. Key customers included multi-billion-dollar retail chains like Ace Hardware, Best Buy Canada, and Overstock.com as well as an assortment of mid-sized merchants including Build.com. Since the company’s software solution scaled effectively from medium to large enterprise businesses, the focus on larger customers was primarily a function of the larger revenues they produced rather than ability-to-serve. Sales effort to acquire a customer was essentially a fixed cost. Several factors had led to a situation where most of the company’s customers were based in the United States and Canada. First, the North American retail market was large and e-commerce highly developed, making pricing data easy to gather and the pool of potential customers large. Second, the predominance of English as the language of commerce had helped to simplify information gathering and reporting from the web and made the sales task easier. Third, the company was able to collect and present pricing in only two currencies, which minimized challenges related to currency translation and fluctuation. Fourth, this focus made it easier to manage relationships across the three major time zones in which most North American businesses were located (i.e., Eastern, Central, and Pacific). Finally, and perhaps most importantly, selling in 360pi’s home markets was logistically more practical and, until recently at least, there had been no shortage of potential business to pursue among North American retailers. COMPETITORS Since pricing intelligence involved gathering and analyzing online data, and then packaging the information and insights for customers, the business could be run from virtually anywhere. 360pi’s competitors were located all over the world, though most had at least a sales office in the lucrative U.S. market. Key rivals included: McKinsey / Periscope. McKinsey was a well-known strategic management consulting firm with a global presence. Its Periscope unit was something of a departure for the company, in that it represented a focused effort to establish a presence in big data and software solutions. Leveraging McKinsey’s global reach of over 100 offices, Periscope promised to provide transparency into big data and insights into competitor strategies to deliver practical recommendations based on advanced analytical algorithms.

360PI: INTERNATIONAL EXPANSION Page 7 Ugam Solutions. Founded in 2000 and headquartered in Mumbai, India, Ugam was a provider of market research, analytics, and online marketing services. The company had sales and service offices in New York City, Dallas, and London, and operations in Coimbatore, Bangalore, and Mumbai. Like 360pi, Ugam targeted large enterprise retailers. The company leveraged its location in India by using low cost labour to manually perform significant aspects of the price intelligence process. This lengthened turnaround time and limited the quality the data, but allowed the company to offer a more customized approach. Dynamite Data / Market Track. Founded in 2005 in Las Vegas, Nevada, Dynamite Data was a 20-employee firm focused mainly on monitoring prices of consumer electronics. In August 2013, it was acquired by Market Track, a Chicago, Illinois-based company with over 400 employees, which monitored Sunday circular advertisements, retail websites, and retailers’ promotional emails to help customers monitor competitive advertising and pricing activity. Profitero, based in Dún Laoghaire, Ireland (a Dublin suburb), concentrated mainly on pricing intelligence for the grocery business; key customers included British grocery giants Tesco and Waitrose, UK online grocer Ocado, and Walmart-owned Sam’s Club. Profitero’s main claim to fame was UK grocery, but they had begun to develop a small presence in North America, mainly in durable goods such as appliances and consumer electronics. Upstream Commerce. Based in Tel Aviv, Israel, with a sales office in New York City, Upstream Commerce mainly served small- and medium-sized retailers. Despite claiming Staples, ToysRUs, Petco, eBags, and Benchmark Brands among its customers, it was generally believed that the nature of the company’s technology limited it from serving large-enterprise retailers effectively. Price Manager. Headquartered in Teaneck, New Jersey, a suburb of New York City, Price Manager focused on providing pricing intelligence to smaller retailers. The company had recently begun a push to expand its customer base to include small manufacturers as well. RETAIL SECTOR TRENDS With the continued rise of e-commerce, and a range of other technical, economic and socio-demographic developments, it was clear that the retail sector was undergoing dramatic change. Among other things, mid-market retail had been shrinking for over two decades, as witnessed by the demise of department stores such as Montgomery Ward and well-publicized struggles at J.C. Penney and Sears. Most growth had been at the high and low ends of the market, with the success of luxury stores like Nordstrom and Whole Foods, and discounters like Walmart, Target and Costco. Moreover, a significant proportion of sales at the low end was moving online, since e-commerce prioritized price and there was very little “service” lost in the shift away from physical stores. A related trend was the transformation of many boutique stores into specialty etailers, thanks to the availability of simple e-commerce solutions such as those offered by Shopify, BigCommerce and Volusion. In addition, “showrooming” was becoming a major challenge for bricks-and-mortar retailers. This referred to the practice of consumers visiting a physical store to examine and compare goods, then using their mobile device to search for—and often purchase—the items elsewhere at a lower price, sometimes while still in the bricks-and-mortar retailer’s showroom. This phenomenon had become widespread in markets with significant e-commerce penetration, making real-time price intelligence relevant even to merchants that lacked significant online operations.

Page 8 360PI: A WORLD OF OPPORTUNITY NEXT STEPS Although there was no specific impetus for change, Rink believed that successful companies were those that actively sought out and capitalized on opportunities. To maintain and enhance its competitive position, 360pi would need to continue to grow. Several options were under consideration as the company contemplated its next move: Attract Additional Bricks and Mortar Retailers One possibility was to focus on attracting additional bricks-and-mortar retailers within product categories the company currently served. Bricks-and-mortar retailers competed directly with their e-commerce counterparts and would benefit from having the pricing information on the same or similar products sold online. Although this business was highly competitive, and offered only modest opportunity for differentiation, 360pi management felt there was room for improvement in the sales process with more extensive outbound calling. The advantage of this approach was that no adjustments would be needed to product or pricing, and new sales staff could simply be incorporated into the existing hierarchy. Expand into Additional Retail Categories Another option was to expand into new categories of retailers, such as grocery / consumer packaged goods, apparel, health and beauty, and/or automotive (see Exhibit 4). Each of these categories would have different needs, so expansion into one did not necessarily imply a move into the others. Grocery, which represented roughly one-quarter of retail sales in North America, was an obvious possibility, especially since Amazon continued to expand its food offerings in the United States. However, e-commerce in the North American grocery sector was still underdeveloped, with significant online players in only the largest cities. This meant that online grocery price data were incomplete and, since conventional grocers relied on weekly ads, dynamic pricing was not yet common. Target Manufacturers 360pi was also considering placing more emphasis on providing pricing intelligence solutions to manufacturers. A few of 360pi’s competitors, such as McKinsey’s Periscope, had already begun moving in this direction. An intriguing dynamic with manufacturers was that they generally had global—or at least multinational—operations. Thus, a focus on manufacturers would be a de facto decision to internationalize since, even if client sales and service were concentrated within Canada and the United States, this would require that prices be monitored across multiple markets and currencies. Based on initial research, 360pi estimated that the global price intelligence market for manufacturers was larger than that for retailers. However, this market was considerably less mature, since manufacturers had traditionally focused on wholesale pricing rather than the way their products were priced at retail. Targeting manufacturers would also require that 360pi learn more about their distinct needs, and how they differed from those of retailers. Reconnect with the Consumer Market Another option, perpetually on the table, was to leverage 360pi’s pricing intelligence software to mount a return to the consumer market, where the company had gotten its start. The business model for this was unclear, but a consumer presence had the potential to provide 360pi with several benefits: Done right, it

360PI: INTERNATIONAL EXPANSION Page 9 would raise the company’s profile. A consumer-targeted service might also make it possible to collect data that would enable 360pi to provide additional insights to business customers, much as Google did in leveraging its suite of services to sell targeted search advertising. International Expansion Regardless of what else the company might do, Rink was confident that a significant opportunity lay in international expansion. The principal challenge of this option was the need to create the infrastructure to sell and service customers internationally. The business development team would need to acquaint itself with unfamiliar markets, and potentially new languages, cultures, and ways of doing business. The challenge would be to figure out how to achieve this without disrupting existing operations. While there would also be technical challenges, 360pi’s software platform was built to be versatile; it could be readily adapted to accommodate multiple languages for data gathering and customer reporting, factor in multiple-currency considerations, and account for cross-border differences in product specs and model designations. Nevertheless, costs involved in making these adjustments would need to be considered. As far as the 360pi leadership team was concerned, international expansion was not a question of if, but when. Many of the company’s customers had multinational operations or, at least, aspired to expand beyond the confines of North America. Moving into new geographic markets, either with or in advance of their customer base, was thus a logical evolution. But they were less certain of the timing, or which countries made the most sense as a starting point—especially if they also decided to broaden their customer base to include manufacturers. There were many variables to consider, ranging from internet and e-commerce penetration (see Exhibits 5-10) to the costs to market, sell and provide service to customers in those markets (see Exhibit 11). Some members of the team felt that the best approach was to start with low-hanging fruit—i.e., those markets that would be easiest to serve. English-speaking markets, such as the UK, Ireland, Australia, and New Zealand, offered one such avenue, since 360pi’s business development team would be comfortable selling to them and customer support would be simple. Another option was to focus on countries in the Americas, which shared similar time zones with Ottawa, had strong ties to the U.S. economy, and were predominantly Spanish-speaking. Arguably the most difficult international markets were those in Asia. Travel was expensive and time consuming, languages were unfamiliar and varied, time zone differentials were substantial, and currencies were different. On the other hand, China was the world’s most populous country, with a rapidly expanding base of consumers and e-commerce retailers. Moreover, this was the market that many of 360pi’s large enterprise customers had flagged for future growth. Given that few of the company’s major competitors had much presence in the Chinese market, perhaps now was as good a time as any to take the plunge.

The Sprott School of Business gratefully acknowledges the generous support of Export Development Canada in the development of these learning materials.

Page 10 360PI: A WORLD OF OPPORTUNITY

EXHIBIT 1: 360PI PUBLIC WEBSITE LANDING PAGE

Source: Company Files

360PI: INTERNATIONAL EXPANSION Page 11

EXHIBIT 2: 360PI LEADERSHIP TEAM Alexander Rink, Chief Executive Officer. Rink had joined 360pi in June 2010. A serial internet entrepreneur and experienced leader, he was adept at guiding new technologies and companies through product and strategy definition, customer development, financing, and profitability. Previously a management consultant with Bain & Company, he also had several years of operational experience leading the Material Control team at Ford/Volkswagen in Europe. Jenn Markey, Vice-President of Marketing. Hired by 360pi in 2013, Markey brought two decades of experience in strategic marketing, product management, and business development, with notable expertise helping early stage companies build their market presence. She had previously held senior technical and management posts with SkyWave Mobile, J2 Global, UBM TechInsights, CrossKeys, Bell Canada International, and IBM. Dominic Plouffe, Chief Technology Officer. 360pi’s first employee, Plouffe had been with the company since 2008. Previously, he had worked as a senior developer for various software firms, including bitHeads, Cre8Object, and Jetform, and had co-founded FuseTalk Inc., which he sold in 2006. Plouffe was the technical visionary behind the company’s software and, with Rink, was co-founder of the successful 2011 shift in the company’s direction. Barry Sexton, Vice-President of Services. At 360pi since January 2012, Sexton had previously served as CEO and Chief Operating Officer (COO) for several Ottawa-based software firms. He brought extensive management experience to the company, as well as familiarity with a variety of markets, including the manufacturing sector, higher education and health care. Source: Company Files


EXHIBIT 3: SAMPLE PRICE INTELLIGENCE REPORT In addition to having access to raw pricing data, 360pi customers could make queries to generate specific reports. Below are samples of real data from the 360pi system, and a discussion of the insights they offer, providing a concrete illustration of how and why a customer might use the data. (NOTE: Black Friday is the day that immediately follows the Thanksgiving holiday in the United States, and is generally recognized as the busiest shopping day of the year in the U.S.)

360pi

Amazon Holiday-Season Shopping Insights Report Black Friday Pricing: Mass Merchants and Specialty Similar to previous years, we see several retailers with increased average prices on Black Friday—November 28—compared to their prices on November 16. This may be a general similarity in mass merchant strategy—Amazon, Walmart and Target all had higher prices on November 28-29 than they did on November 16. Sears also seems to be following this trend. And, as we have seen in numerous other reports in the series, overall, Walmart has been step in step with Amazon this holiday season. Specialty retailers, however, appear to have a different strategy. Lowe’s and Home Depot both dropped prices significantly heading into Black Friday compared to their prices in the previous week. Macy's and Bed Bath & Beyond also had significantly lower prices on November 28 as compared to November 16. We will keep an eye on whether the specialty retailers raise prices post Black Friday or continue their discounts in the weeks to come.

360PI: INTERNATIONAL EXPANSION Page 13 Small Appliances: Category-Specific Volatility Small appliances were in the spotlight this Black Friday as a popular gift item. We saw that it was one of the more price-volatile categories among our sample set and average prices on available products did go down on Black Friday at most sampled retailers.

In this category, Walmart is exhibiting the most volatility among the retailers in the sample. To help explain this pattern, we look at Walmart’s price on one coffee maker in particular. How many of their Black Friday special deals have exhibited a similar pattern?


We compared the average retailer price difference from Amazon on the overall 10-category sample to the delta observed in two specific categories—small appliances and toys—to highlight category-specific differences in holiday pricing strategies. As the charts below indicate, toys was a highly contested category exhibiting a much narrower price than average between Amazon, Walmart, and Target, while small appliances had a higher than average price spread. On Black Friday itself, competitive pressure in toys continued to be extreme, with Amazon dropping prices more aggressively than Walmart and therefore regaining some of the competitive pricing gap.

Source: Company Files


EXHIBIT 4: GLOBAL RETAIL SALES VOLUME BY PRODUCT CATEGORY

Category

Online Sales by IR500 Merchants

(US$ billions)* Offline Sales

(US$ billions)** Total Category Sales

(US$ billions) Apparel 25.4 198.6 239.0 Auto Parts 1.1 76.2 83.0 Books/Music/Video 16.7 24.5 43.0 Building/Hardware/Home Renovation 4.0 529.8 573.7 Electronics 23.7 212.3 252.0 Food & Drug 4.8 797.4 862.2 Mass 67.7 524.8 632.0 Health & Beauty 4.6 251.4 274.9 Housewares/Home Furnishings 5.6 124.1 139.0 Office 18.9 17.9 38.1 Sporting Goods 2.9 36.9 42.6 Toys/Hobbies 2.6 15.7 19.5 * IR500 Merchants = Top 500 e-commerce retailers by global sales. ** Offline figures include direct marketing, TV and catalog sales. Source: InternetRetailer.com


EXHIBIT 5: INTERNET PENETRATION RATES BY COUNTRY

Europe North America

Austria 80 US 78 Belgium 81 Canada 83 Bulgaria 51 Croatia 71 Latin America Czech Republic 73 Argentina 66 Denmark 90 Brazil 46 Estonia 78 Chile 59 Finland 89 Colombia 60 France 80 Mexico 37 Germany 83 Peru 37 Greece 53 Venezuela 41 Hungary 65 Ireland 77 Asia-Pacific Italy 58 Australia 89 Latvia 72 China 40 Lithuania 65 Hong Kong 75 Netherlands 93 India 11 Norway 97 Indonesia 22 Poland 65 Japan 80 Portugal 55 Malaysia 61 Romania 44 New Zealand 88 Russia 48 Philippines 32 Serbia 56 Singapore 75 Slovakia 79 South Korea 83 Slovenia 72 Taiwan 75 Spain 67 Thailand 30 Sweden 93 Vietnam 34 Switzerland 82 Turkey 46 Mideast & Africa UK 84 Egypt 36 Ukraine 34 Israel 70

Pakistan 15 Saudi Arabia 49 South Africa 17 United Arab Emirates 71

Source: Internet World Stats, June 30, 2012


EXHIBIT 6: E-COMMERCE PARTICIPATION RATES BY COUNTRY Percentage of internet users aged 14+ who made at least one purchase online via any digital channel during the calendar year.

2011 2012 2013 2014 2015 2016 2017

North America 68.9 70.5 72.0 73.6 74.9 76.3 77.7 United States 70.3 71.6 73.0 74.4 75.6 77.0 78.4 Canada 56.9 60.8 63.1 66.2 68.9 70.1 71.0

Asia-Pacific 40.7 42.3 44.6 47.1 50.2 52.5 54.2 Japan 74.3 76.8 78.3 79.0 79.8 80.4 81.0 Australia 74.0 74.7 76.2 77.6 78.6 79.1 79.7 South Korea 67.0 69.1 71.1 73.0 74.9 76.0 77.0 China 39.5 43.7 49.3 55.2 61.7 67.0 71.0 India 22.5 22.9 23.5 24.4 26.0 27.0 28.0 Indonesia 6.0 7.8 9.5 11.0 12.0 12.6 13.0 Other 31.1 30.9 31.0 31.5 32.7 33.3 34.0

Western Europe 67.2 70.1 72.3 73.5 74.4 75.4 76.3 UK 82.5 85.0 87.2 88.0 88.2 88.9 89.0 Germany 75.1 78.7 80.8 81.6 82.3 83.0 83.8 Denmark 73.6 77.1 80.7 80.8 81.6 82.0 83.6 France 71.1 75.3 78.1 79.2 79.1 79.2 79.4 Sweden 73.4 74.8 76.3 76.8 77.8 78.7 79.6 Netherlands 71.3 73.8 74.6 75.0 75.9 76.0 76.2 Norway 71.3 72.3 73.6 75.5 77.7 80.2 83.0 Finland 66.2 67.2 68.4 70.3 72.5 74.9 77.0 Spain 49.6 51.9 54.5 57.0 60.0 62.0 64.0 Italy 38.5 41.3 44.1 46.3 48.7 51.0 53.0 Other 66.8 69.8 72.2 73.3 74.3 75.3 76.1

Eastern Europe 37.1 39.8 41.6 43.4 44.3 44.4 44.6 Russia 35.3 38.0 39.7 41.6 42.5 42.5 42.5 Other 38.0 40.8 42.5 44.3 45.2 45.4 45.6

Latin America 28.2 31.6 33.0 34.4 35.4 36.3 37.2 Argentina 38.2 43.9 45.7 47.4 48.3 49.0 49.7 Brazil 30.0 34.0 36.0 37.7 39.0 40.0 41.5 Mexico 18.3 19.6 20.4 21.3 22.3 23.3 24.0 Other 28.2 32.3 33.7 35.1 36.1 36.9 37.8

Mideast & Africa 25.3 29.2 31.3 33.1 34.0 35.0 36.0 WORLDWIDE 38.0 39.2 40.4 41.6 43.0 44.1 45.1 Source: eMarketer, June 2013


EXHIBIT 7: BUSINESS-TO-CONSUMER E-COMMERCE SALES: US$ BILLIONS

2011 2012 2013 2014 2015 2016

North America 327.77 373.03 419.53 469.49 523.09 580.24 United States 308.64 351.80 395.28 441.95 492.07 545.81 Canada 18.58 21.23 24.25 27.55 31.02 34.43

Asia-Pacific 237.86 315.91 388.75 501.68 606.54 707.60 China 56.69 110.04 181.62 274.57 358.59 439.72 Japan 112.90 127.82 118.59 127.06 135.54 143.13 Australia 22.86 25.26 26.77 28.31 29.76 31.24 South Korea 16.34 17.32 18.52 20.24 21.92 23.71 India 8.68 12.12 16.32 20.74 25.65 30.31 Indonesia 0.56 1.04 1.79 2.60 3.56 4.49 Other 19.84 22.30 25.14 28.16 31.53 34.99

Western Europe 218.27 255.59 291.47 326.13 358.31 387.94 UK 76.75 87.25 99.19 111.30 122.68 132.80 Germany 38.08 47.00 53.00 58.00 62.00 66.00 France 29.68 33.33 36.99 40.35 43.57 46.88 Spain 15.64 18.57 21.57 24.54 27.46 30.21 Italy 12.88 16.16 19.80 23.81 27.80 31.25 Netherlands 7.01 7.99 8.98 9.89 10.78 11.50 Sweden 5.32 6.30 7.32 8.29 9.14 9.96 Norway 4.97 5.82 6.71 7.60 8.40 9.02 Denmark 5.16 5.90 6.63 7.33 7.98 8.50 Finland 3.29 3.82 4.38 4.87 5.31 5.69 Other 19.50 23.45 26.89 30.14 33.19 36.15

Eastern Europe 30.89 40.17 48.56 57.96 64.35 68.88 Russia 11.14 14.48 17.54 20.92 23.17 24.78 Other 19.75 25.69 31.02 37.04 41.18 44.10

Latin America 28.33 37.66 45.98 55.95 63.03 69.60 Brazil 13.92 16.95 19.74 23.51 25.52 27.28 Mexico 4.18 6.16 7.98 9.88 11.40 12.92 Argentina 2.57 3.36 3.86 4.79 5.65 6.33 Other 7.66 11.19 14.40 17.77 20.46 23.07

Mideast & Africa 14.41 20.61 27.00 33.75 39.56 45.49 WORLDWIDE 856.97 1042.98 1221.29 1444.97 1654.88 1859.75

Source: eMarketer, June 2012


EXHIBIT 8: ONLINE BROWSING INTENTIONS BY REGION Percentage of population aged 14+ who expected to browse the internet for information on products from the specified category sometime within the next six months.

Asia-Pacific Europe Mideast /

Africa Latin

America North

America Clothing, Accessories and Shoes 49 37 32 54 50 Electronic Equipment 43 36 37 62 42 Tours and Hotel Reservations 44 33 34 52 44 Airline Tickets and Reservations 43 31 35 49 44 Mobile Phones 41 33 40 61 33 Event Tickets 39 31 31 48 38 Computer Hardware 39 32 35 51 37 Hardcopy Books 40 29 30 48 34 Computer Software 36 26 35 50 34 E-books 39 23 35 45 33 Sporting Goods 39 25 27 47 29 Music (not downloaded) 36 25 30 47 30 Videos, DVDs and Games 35 25 30 47 34 Cosmetics 39 24 26 42 24 Personal Care 38 20 26 40 19 Groceries 37 19 22 37 19 Toys and Dolls 33 18 24 35 25 Cars, Motorcycles and Accessories 26 24 27 53 25 Pet-Related Products 25 17 20 36 23 Baby Supplies 28 13 23 32 13 Flowers 22 11 20 26 23 Alcoholic Drinks 26 10 12 27 10

Source: Nielsen Global Survey of E-Commerce, Q1 2013


EXHIBIT 9: ONLINE BUYING INTENTIONS BY REGION Percentage of population aged 14+ who expected to make an online purchase of at least one product from the specified category sometime within the next six months.

Asia-Pacific Europe Mideast /

Africa Latin

America North

America Clothing, Accessories and Shoes 57 34 26 28 42 Electronic Equipment 41 25 26 29 30 Tours and Hotel Reservations 53 33 35 32 43 Airline Tickets and Reservations 59 34 39 36 43 Mobile Phones 44 22 28 27 22 Event Tickets 50 33 28 31 35 Computer Hardware 36 23 25 20 29 Hardcopy Books 50 30 22 24 31 Computer Software 33 19 27 18 27 E-books 43 22 29 23 35 Sporting Goods 42 19 20 19 21 Music (not downloaded) 33 19 21 19 30 Videos, DVDs and Games 32 21 23 21 33 Cosmetics 43 21 19 20 21 Personal Care 43 17 18 14 16 Groceries 41 14 15 11 14 Toys and Dolls 40 16 18 17 24 Cars, Motorcycles and Accessories 20 13 16 11 15 Pet-Related Products 26 15 14 11 19 Baby Supplies 29 12 16 11 12 Flowers 21 11 16 10 21 Alcoholic Drinks 25 9 11 8 10



EXHIBIT 10: DEVICE USAGE FOR ONLINE SHOPPING

Computer Smartphone/

Mobile Device Tablet Asia-Pacific 81 52 35 Europe 78 33 24 Latin America 82 48 29 Mideast / Africa 60 55 38 North America 84 27 26

Global Average 80 44 31


EXHIBIT 11: COMPETITIVE LANDSCAPE RETAIL PRICE INTELLIGENCE INDUSTRY

North

America UK /

Ireland Eurozone Australia /

New Zealand Latin

America China Population (millions) 355.5 70.5 429.5 28.2 604.0 1,357.4 GDP growth 2.5% 3.2% 1.3% 2.7% 1.2% 7.3% Maturity of e-commerce high high high high low moderate Level of competition: (pricing intelligence) high high high high low low

Cost to serve low moderate moderate moderate moderate very high

Source: Company files

360PI: A WORLD OF OPPORTUNITY · Periscope.” The news came as something of a surprise: Although Vienna-based Lixto was one of Europe’s most highly-regarded pricing intelligence

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