Buckner (Site Selection, 2010, Chapter 2) describes both "location" and "site" as market concepts that are rich with broad sets of data to characterize these geographic entities. In Lesson 3, your initial inquiry into the market you selected should have demonstrated the breadth of possible viewpoints one can use for market exploration and analysis. Site selection, therefore, can be amply supported by vast sources of relevant data. The challenge to make this business analysis useful to a company becomes choosing the right factors to analyze and in which combinations. It's important in our research, writing, and discussions to use appropriate synonyms for selecting the "right" place for a new store. Will there always be one, right place for a new coffee shop? Or, as a location intelligence professional, could we clarify that the results show a business owner that site x optimizes the criteria they provided ... or this site maximizes foot traffic, increases your company access to Gen Z customers, or reduces the tax burden for a new store like they desired?

Here, Church's 3 Laws of Location Science guide the market analyst to selecting the best suited data. These simple rules help us to home in to the most important criteria to pick among the vast repositories available. The result will be more efficient and effective analyses (Church, pp.8-9).

1. Some locations are better than others for a given purpose. This raises questions to determine how to select the "best" location; how does efficiency fit in for the business and customers traveling to buy goods?
2. Spatial context can alter site efficiencies. Proximity isn't always how consumers choose to shop. Often, they're attracted to clusters of businesses that offer many products or services they choose.
3. Sites of an optimal multisite pattern must be selected simultaneously rather than independently, one at a time. What? Church shares the example of setting up a chain of pizza stores that guaranteed 30 minute delivery or the pizza was free. To cover a town or city geography, the site selection of one pizza store is dependent on the network that business establishes.

Before we settle into our data selections, we will expand our perspective further by exploring a second data source, the Esri Tapestry geolocation segments. While the Tapestry data is similar to the Nielsen PRIZM data in its purpose, the two sources provide unique points of view on similar underlying historical data. In this lesson, comparing and contrasting alternative geographic data will expand our analytical perspectives and prepare us for insightful analysis using GIS systems such as Esri's Business Analyst Online (BAO).

There's an important tenet of providing a unique customer experience. A company's effort should focus on solving a consumer's need with a product or service, drawing customers to your business, and creating a satisfying experience to build loyalty.

What is due for Lesson 4?

Lesson 4 will take us one week to complete. There are a number of required activities in this lesson listed below. For assignment details, refer to the lesson page noted.

Note: Please refer to the Calendar in Canvas for specific time frames and due dates.

Requirements for Lesson 4

Competition

In striving to gain a market dominance or preference, businesses create advantages for their organization and consumers. The process drives competition and innovation to meet customer needs; often improving products or services beyond the initial designs of a company's plan. Companies analyze their market and improve strategies to gain advantages or disadvantage competitors. Interestingly enough, competition can be defined as seeking to gain or win something and contending for an achievement. Competition appears in multiple forms or environments:

1. A business Competitor, such as a corporation, firm, or commercial organization.
2. Competition between entities, look at the pharmaceutical company direct-to-consumer (TV and Digital) advertising, or
3. Competitive environment, a market sector

Buyers, when purchasing goods or services, seek a simpler, more customized experience to select products and services that meet their particular needs. Many buyers may have exactly the same needs; but it's their choice to select where they shop, who they buy from, and which product(s) they select. A business designs products to meet needs and preferences, analyzes consumer behaviors to determine where to attract customers, and performs extensive business analysis to organize the retail experience.

Relating back to the principles of commerce, there are strategies to leveraging competitive factors in business in order to achieve an advantage:

1. Business optimization and improving an organization to be the most attractive for customers to conduct their transactions
2. Customer experience, to enjoy shopping or encounter the least pain to find the product one's seeking
3. Financial improvements of decreased costs, increased reach to high potential customers, decreased ineffective customer leads, increased sales, or increased profit margins.

Competitive Location Data

Location analysis explores geospatial and business data to determine where to locate a business. Data is widely available and at times expensive. One must decide what is important about the geospatial and business data a company seeks; what level of detail, precision, and current information is needed. A business may use general marketplace information for strategic decisions or highly detailed to make a critical investment decision. Assumptions made in the early stages of business analysis are based on relevant information; and accurate geospatial information adds credibility to the stated assumptions.

Where - in what retail environment does a business sell products to its customers?

1. At a physical site, e,g, brick-and-mortar, Big Box, or retail store, or
2. Through e-Commerce, where products are shipped from the locations of business functions.

An online location can also be defined and optimized by selecting the best domain name for the business, launching online advertising campaigns, and employing search engine optimization (SEO) so consumers can find your business. SEO is a fundamental principle of online retail to attract as many potential buyers to a business website and e-Commerce applications.

To understand consumer behaviors and model their buying patterns, business location analysis also considers demographics, psychographics on consumer behavior, census, market information on channels and products, and geospatial data. Later lessons in the course introduce omni-channel marketing plans, use of technology and IoT to interact with customers, and integrated market research.

Companies develop tools and build databases for their Operations and Marketing professionals to view business functions in a similar format with the latest actionable data. Analytical tools include dashboards, ad-hoc analytics, extensive modeling and customer graphs. The Data Environment spans:

1. Customers
2. Marketing
3. Channel
4. All Sales and Service Interactions

Geospatial analysts have a role in predictive and prescriptive analysis for a business to identify the structure for their sales, product portfolio to meet customer needs and maximize profits, and decide between competing priorities facing the company in a competitive marketplace. Predictive analysis for location intelligence is based on modeling geospatial and business information to answer a business question. Other analysts in business departments, e.g. Marketing, Business Analytics, Operations, conduct business forecasting and strategic planning using similar or different data with more focus on quantitative results than geospatial relationships. One objective of this course is to expand the knowledge, modeling skills, and experience of geospatial data scientists to provide value across an organization's structure.

One could say, "businesses measure everything." Modern companies collect data on every transaction, each event in the manufacturing process, and consumer behaviors that may impact the products the company builds. Third-party data providers collect and analyze Big Data in enterprise and relational databases, preparing reports - or access to structured data - for businesses to purchase. This saves effort and, possibly, money for a business to gain the market and consumer data they specifically require to stay relevant.

Customer relationship management (CRM) is a business of itself with software, products, dashboards, interfaces for sales and marketing, and connections to marketing campaigns. CRM always has a location component; providing a linkage of business and geospatial data to produce location intelligence. A known customer who willingly or passively provides purchasing data assists a business in market studies. Consider the questions a business may ask to understand, quantify, or verify their market position compared to competitors. Third-party providers detail and summarize consumer behavior to relate:

• Which marketing message a customer viewed and the products they recently purchased,
• How many competitor's products the customer purchased and whether they bought from this business,
• Where the customer purchased different items, the volume and frequency of shopping, how many items/sale at various store locations,
• Through demographics, what group is a customer most similar to?

Every encounter with a potential customer costs a business money; whether that is through marketing, paying employees for extended hours, answering detailed customer questions, providing live customer-service, or reorganizing retail spaces to address consumer changing preferences. A current CRM provides the business detailed information about customer behaviors for market and location intelligence analysis. To understand the value of using their own customer's information, a business must only look at the wasted dollars spent on direct mail advertising campaigns that never attract a new customer or digital ads on Social Media platforms where users click "Skip Ad" and rarely access the company's product website.

A valid customer lead, pre-vetted contact information, or request for contact from a potential customer provides a company advantages over their competitors. The challenge is to recognize these leads, respond to customers, and provide the products they need or desire.

Trade Areas

For a community, a trade area is an economic zone with generalized or defined geographic boundaries. This is a region where commercial organizations conduct business, where stores are sited for customers to purchase goods, business entities lease or own space to engage with clients and perform services, or buildings are erected to offer space to attract commerce. A trade area may be determined by the farthest distance a consumer is willing to travel to purchase goods they need; communities often designate trade areas in a convenient location for citizens to purchase goods or services (optimizing time, effort, and value).

Two common methods of defining and mapping trade areas examine radial distance-based concentric rings and travel time-based irregular shaped polygons. The method for analyzing trade areas often includes existing customers, competitors by locations and products, and the geographic distribution of potential customers who would travel to the shop or receive delivered goods in the trade area (Horan, 2022, pp.72-75).

Murphy (2018, p.36) describes a geographer's approach to spatial arrangements:

They seek to identify and explain the significance of spatial patterns. They explore what variations across space tell us about the forces shaping biophysical and human processes. They investigate the nature and meaning of interconnections across space and scale. And they look critically at the spatial ideas and frameworks humans use to understand, navigate, and seek to change the world around them.

Site Characteristics

Buckner relates how site characteristics describe the qualities of a location rather than quantitative measures. While there is amazing competition between retailers over the "best" anchor position in a shopping mall, human factors significantly impact the potential sales of a business location. Detailed market studies consider all factors to include visibility for consumers, parking, accessibility to shop for products; and most importantly, assess the context and relation of characteristics to the community (Buckner, pp.70-73).

We find value in examining variations from place to place. Murphy discusses the interconnections across space and scale for readers to understand that a site, a store, or an event exists in relation to other places or factors. Studying the attributes of one individual place reveals a response or adaptation from the characteristics of another, proximal space. Communities and economies depend on trade, customers, competition, and development. Question how a trade area expanded in an area of the city, why certain shopping areas are busier or more profitable than others, and where consumers may prefer to shop in the future. Thinking critically of geography, technology, mobility, and human behavior, Murphy writes:

Another revolution in mobility and connectivity is looming - driven not by a single transformative invention but by a suite of technological innovations and social-environmental concerns that are likely to have profound consequences in the years ahead: driverless cars, electric vehicles of various sorts, ride-sharing, super-high-speed trains, and an increasingly pervasive internet. Collectively, these will influence how billions of people experience and comprehend the world around them.

One way to investigate "the competition" is to determine other businesses which fall into the same classification as our business of interest. Buckner mentions Standard Industry Classification (SIC) codes in the readings. The North American Industry Classification System (NAICS) replaced SIC for the 2002 Economic Census and going forward (and correlates to codes used in the 2020 United States-Mexico-Canada Agreement (USMCA) (formerly North American Free Trade Association, or NAFTA). In your exploration of business classification, investigate NAICS and related topics:

1. Review the "Introduction" to the North American Industry Classification System (NAICS) on the US Census Bureau website.
2. Using the 2022 NAICS Search tool on the same page, identify the NAICS code for the business you select in the Do: Site Visit to Your Selected Business activity below.
3. The US Government discontinued use of the Standard Industry Classification (SIC) groupings in 1997. While SIC codes have been replaced by NAICS, you'll still find instances where knowing a SIC code, or how to find it, is valuable.
4. You may also reference the System for Award Maintenance (SAM) for additional information on NAICS, DUNS, and legal name for commercial entities doing business with the US Federal Government.
5. OPTIONAL: Returning to the 2022 NAICS Main page, locate the North American Product Classification System (NAPCS). Skim though NAPCS material until you can answer the following question—what is the value of NAPCS if we already have NAICS?

As a Personal Activity, complete a virtual Site Visit to Your Selected Business

Consider this activity our virtual class "field trip"—one which you'll do independently, however. You are selecting a site location, so choose something interesting; (but starting in 2020 with COVID-19 in mind), you are definitely not required to physically go to any retail establishment or store.

If you are performing a remote drive-by reconnaissance, make sure you have a way to take notes and photos with your smartphone or digital camera.

1. Choose a nearby location of one of the following retailers (preferably one that you actually shop at!): Best Buy, Target, Albertsons Companies supermarkets, Bed Bath & Beyond (Ch. 11), ACE, Lowe’s (or some other national retailer with which the class will be familiar).
2. Complete the sample "site evaluation form" in Figures 5-2 and 5-3 (Buckner, Site Selection, Chapter 5).
3. Add to the form comments about accessibility, "synergy," and safety/security from the reading.
4. Obtain images through a web search, take a picture of the site, or sketch a diagram/capture a map which illustrates a point you wish to make - likely about parking, signage, synergy/adjacency to other retailers.

Psychographic/Behavioral Analysis and Incorporate Reports

Follow this optional exercise to hone your BAO skills, gain additional insights to a location intelligence platform, or use to expand your understanding of site selection.

Using BAO, return to your analysis/critique of your Claritas PRIZM results. You're going to add to the demographic work you did in section 3.3 of Lesson 3 by looking at Tapestry Segmentation, amongst other reports.

Your goal here is to further strengthen the argument you made last week concerning the accuracy or inaccuracy of your Claritas PRIZM results. Again, I recommend you focus on your PRIZM segment(s) to keep this analysis simple. Also, please make sure you start with ZIP code data, only turning to smaller level geographies, if you wish, to underscore your argument.

Requirements:

• Run at least two reports for your ZIP code level analysis.
• Run a "Tapestry Segmentation Area Profile" report on your ZIP code to rank the segments which make up your specific ZIP code. Use this report to identify top segments and make your comparisons to your Claritas PRIZM results.
  • NOTE: to be fair to the oversimplified Claritas PRIZM "You Are Where You Live" tool, please focus on the top 5 Esri Tapestry segments first. Don't forget; your Claritas PRIZM results were NOT ranked, but delivered to you in alphabetical order.
  • If you took issue with the ZIP code level results of the PRIZM tool, run the "Tapestry Segmentation Area Profile" on your tract and/or block group and see if your results (segments) more accurately match YOU.
  • In comparing your Tapestry segments to PRIZM segments, don't forget to consider how Tapestry's "Urbanization" and LifeMode" segment groups compare to PRIZM's "Social" and "Lifestage" segment groups.

Suggestions:

• As you learned in Part II of your BAO orientation, "Market Profile" and "Executive Summary" are good places to start; they characterize your geography (and will quickly highlight the demography you investigated last week).
• You may have identified one purchasing/buying choice ("these people all drive SUV's") in your Claritas PRIZM segment which you questioned; there may be a report in "Consumer Spending" or "Business" which further validates your position.
  • "Retail Goods and Services Expenditures" may provide insight, as might others.
  • The "Market Potential" reports show you likelihood of specific purchasing/spending behaviors in particular categories.
• As a comparison of your ZIP code's dominant Esri Tapestry segments with your ZIP code's dominant Claritas PRIZM; make sure you're comparing "top 5" to "top 5." Use these questions to help:
  1. How similar was/were the top segment(s) in the two systems? Consider the names of the segments and the demographic/psychographic attributes the systems claim for each.
  2. Was your ZIP code accurately portrayed in Tapestry?
  3. If you didn't feel that the top 5 Claritas/Tapestry segments matched you personally, was there a segment further down the list that did? What proportion of your ZIP code is "your" segment?
  4. If you looked at segments at the tract or block group level, were your results more accurate?

Because this is an optional activity, there is no deliverable for 4.3.

Read the following carefully—you may wish to print this page out to use as a checklist as you complete items.

In this semi-scripted activity, you'll have a chance to practice some of the research skills you have developed so far and practice presenting your results clearly and concisely to your classmates. In addition, this activity should serve as good practice for the term project you will complete during Lessons 5-10 of the course.

Activity Scenario: Locating a Coffee Shop in Atlantic City

You are a geospatial analyst for a small consulting firm based on the East Coast--"Retail Research" with experience in location intelligence studies. Clients Jay and Kay contacted you about starting a coffee shop business in Atlantic City, NJ. They are targeting the seaside resort of Atlantic City and would like to open a franchise. The entrepreneurs have been loyal customers of the specialty coffee chain "Campfire Coffee," a cowboy-themed coffee shop which has successful franchises located primarily in the western cities of Denver, Phoenix, Albuquerque, El Paso, Austin, and San Antonio. They are friends with the Campfire Coffee V.P. of Franchise Marketing. All think the time is right to attempt a location on the East Coast and agree that the raucous gaming town of Atlantic City might be a good place for a location, especially considering the flashy or gaudy nature of Atlantic City. Your job is to perform the initial phases of market research and analysis for Jay and Kay.

To help direct your research, the entrepreneurs have already done some legwork. Having spoken to both the local chamber of commerce and the region's business development office, they are considering two possible areas of location in and around Atlantic City:

1. a walk-in style coffee house in the central business/tourist district of Atlantic City
2. a drive-through location in adjacent Pleasantville. (Local residents and long-term vacationers either live in or drive through Pleasantville regularly on their way to the core of Atlantic City.)

Campfire Coffee is not ready to choose a specific site, so you needn't consider site characteristics such as strip mall or stand alone, lease options, or the like. Rather, they want to make sure that the location meets their basic trade area criteria. While they are not ready to make a site-specific decision, the group is willing to consider any specific sites if an obvious candidate shows up in your research.

Guidelines

The following guidelines MUST be incorporated in your analysis.

• Campfire Coffee has had equal success with both walk-in and drive-through coffee shops, so either concept type is an option. Consider both possible areas of location.
• Campfire Coffee prefers locations where relevant market potential indices (MPI) are, for the most part, greater than the US average.
• Campfire Coffee is generally only interested in locations where there is a market demand (Esri BAO calls this "leakage").

First, you must decide before continuing if you’re recommending a location (1) or (2):

1. close to direct competitors in a clustering approach [ICIC ], leveraging economy of scale and concentrations of customers,

or

2. at a distance away from competitors to gain a competitive advantage, drawing coffee drinkers to your site.

Then, are you recommending a walk-in location or a drive-through location?

For a possible walk-in location:

• will only consider along Atlantic Boulevard or to the south (towards the ocean/beachfront) in the boardwalk/casino district, roughly bounded by Albany Ave to the west and New Jersey Ave to the east.
• should be located at least .25 miles (0.4 km) away from any competitor (Starbucks, Dunkin Donuts, etc.).
• should be located at least .25 miles (0.4 km) away from any Atlantic City casino/hotel. (The chamber of commerce informed us that all Atlantic City casinos/hotels have coffee shops/espresso stands located inside, hence casinos/hotels are also competitors in this scenario.)

For a possible drive-through location:

• will consider anywhere in Pleasantville City (proper, within the municipal boundaries or immediately adjacent).
• must be located at least 1 mile (1.6 km) away from any direct competitor (Starbucks, Dunkin Donuts, etc).
• must be located on or very near (around the corner from) an arterial street with an average daily traffic volume (ADT) greater than 15,000.

Suggestions/Hints

• While YOU are the consultant working on this analysis for Jay & Kay, you're welcome to ask any of your colleagues (e.g., your classmates!) for thoughts/help/suggestions. There's not a Discussion page to post a comment. If you wish, you can email All Students and Instruction in this GEOG 850 Section.
• Don't forget about the very helpful, and easy to navigate "Help" for BAO, accessed in the upper right-hand corner of your BAO interface.
• In searching geographies, you may find it easier to draw a polygon when you have an imposed trade area (such as the "boardwalk/casino district" indicated above).
• You can practice by following the instructions below for creating a polygon (and managing your sites) for State College, PA (Fig. 4.1):
  • Log into Esri's BAO site.
  • Create a new "Project."
  • Select the "Maps" tab.
  • Choose the tab "Define Areas for Reports."
  • "Find location" and search for State College, PA.
  • Again choose the tab "Define Areas for Reports", then "Draw a Polygon" (if you have a basemap other than streets, it may not allow you to zoom in to an effective scale).
  • Select the "Polygon" button and draw a polygon around the Penn State campus (see Figure 4.1 below). There is an instructional video available on the BAO webpage if you need assistance.
  • Name the polygon as "Penn_State_Univ" when you finish closing the polygon.
  • Open your Project and all of the files will be in that project.
  • Note: There are a number of help documents and instructional videos throughout the BAO site. Be sure to take a few minutes and look them over as they are very helpful.

Figure 4.1: Polygon for State College Campus as an example of a Trade Area

Credit: Esri Business Analyst Online

• "Retail Market Potential" and "Restaurant Market Potential" reports are great sources for market potential indices (MPI).
• The "Traffic Count Map" report is a great resource for determining average daily traffic (ADT) volume.
• Use "Custom Data Setup" after selecting the "Add Data" tab to locate your competitors. By zooming your map in to only your area of interest, your competitor search will be limited to the viewed extent. In the search bar, you have many options for example InfoGroup July 2016. NOTE: Under "Advanced Search Options" you can search by NAICS Code or keyword. Lastly, your search may produce some results (especially if you use keywords) that you may not wish to consider as competitors—make sure you uncheck those before adding a point layer to your research.
• You can practice by following the steps below for "Business Search":
• Let's examine the competitive business sites using Esri’s Business Analyst Online (BAO). In particular, we will look at coffee shops in and around Penn State University Main Campus.
• The Census Bureau uses the North American Industry Classification System (NAICS) to classify businesses for the purpose of collecting and analyzing data. Additional information can be found on the NAICS site.
• Log into Esri's BAO.
• Go to the " Penn_State_Univ" Project.
• Proceed to the Maps tab, create maps from data, Business and Facility Search, show more options.
• In the “Search Extent” field, choose “Current Map Extent” to get a better image of the area around campus.
• Now we need to search for a type of business. For this exercise, it will be coffee shops.
• To search for the NAICS number for coffee shops:
  • Select the NAICS Code directory link within “Search for a business or a facility.” (Please note that the US Census site provides the NAICS codes for different years in case you have old codes that need updates.)
  • Choose (72, Accommodation and Food Services).
  • Coffee shops would fall under the “Snack and Nonalcoholic Beverage Bars” category so the NAICS number would be 722515.
  • Select (722515, Snack and Nonalcoholic Beverage Bars) to show additional information and a breakdown of business types within that category are available by selecting the “722515” link.
  • Continue with the search, for NAICS Code, enter 722515.
  • Select the “Go” button (See Figures 5.2 and 5.3 below).
• From this point, you can further filter out your search results by unchecking categories from the search results, limiting by the number of employees, or by sales volume.  
• Click next and give your search a name to save it for future reference.
• Suggestion: You may want to think about building rings around your competitor points to help you visualize possible sites.
• If you do locate a desirable site, building rings, drive-times, or donuts around a candidate site could provide further insight.

Caveats

• There isn't a single "correct answer." Your results will depend upon how you chose to evaluate the market (level of geography, variables, etc.).
• Any case study is bound to contain some obstacles unlikely to be encountered "in the real world"—in the real world, you could ask questions of the entrepreneurs, and hopefully you would have access to some kind of comparative store data. Don't let this deter you—make the best recommendation with the information at your disposal. And don't hesitate to be creative—you're welcome to use functions of BAO beyond the aforementioned.

This week, you must organize your thinking about the term project by developing your topic/scope from last week into a short proposal.

Submit a brief project proposal (1 page) to the assignment box. This week, you should start to obtain the data you will need for your project. The proposal must identify at least two likely data sources for the project work, since this will be critical to success in the final project. Over the next few weeks, you will be refining your proposal.

Your proposal should include:

Abstract:

• In brief terms, introduce your project and possible outcomes.
• We'll review formats and effective ways to write abstracts through additional lessons.

Background:

• What is your business question which will benefit from location intelligence?
• Some background on the topic, particularly why it is interesting
• What, specifically, do you hope to find out?
• Geographical scope, scale, and location(s)

Methodology:

• Data: list and discuss the data required to answer the question(s). Be sure to clearly explain the role each dataset will play.
• Be sure to list where you will obtain the required data. This may be public websites or perhaps data that you have access to through work or personal contacts.
  • Obtain and explore the data: attributes, resolutions, scale.
    • Is the data useful or are there limitations?
    • Will you need to clean and organize the data in order to use it?
• Analysis: what you will do with the data, in general terms
  • What sort of statistical analysis and spatial analysis do you intend to carry out? Skim through the lessons to identify the methods you will be using. If you don't know the technical names for the types of analysis you would like to do, then at least try to describe the types of things you would like to be able to say after finishing the analysis (e.g., one distribution is more clustered than another). This will give me and other students a firmer basis for making constructive suggestions about the options available to you. Also, look through the course topics for ideas.

Expected Results:

• What maps, visualizations, tables, graphs, or outputs will you create?

References:

• References to papers you may have cited in the background or methods section. Include URLs to data sources here (if you didn't include the URLs in the Data section.
• The proposal does not have to be detailed at this stage. Your proposal should be no longer than about 1 page. Make sure that your proposal covers all the above points, so that I (Lesson 3 & 4) and others (Lesson 5 – peer review) evaluating the proposal can make constructive suggestions about additions, changes, other sources of data, and so on.
• Additional writing and formatting guidelines are provided in the document (TermProjectGuidelines.pdf) in 'Term Project Overview ' in Canvas.
• You will need a Reference/Bibliography in your report. I recommend starting with proper citations at this time, it will save effort for future assignments.

Refine your work and post a final proposal to the 'Term Project Discussion' board as plain text.

As you all finalizing your project proposals, consider the following aspects:

• Are the goals reasonable and achievable? It is a common mistake to aim too high and attempt to do too much. Suggest possible amendments to the proposals' aims that might make them more achievable in the time frame.
• Are the data adequate for the task proposed? Do you foresee problems in obtaining or organizing the data? Suggest how these problems could be avoided.
• Are the proposed analysis methods appropriate? Suggest alternative methods or enhancements to the proposed methods that would also help.
• Provide any additional input that you feel is appropriate. This could include suggestions for additional outputs (e.g., maps) not specifically mentioned by the author, or suggestions as to further data sources, relevant things to read, relevant other examples to look at, and so on.
• Begin drafting an Abstract for your project. There are various ways to effectively write an abstract that effectively captures a reader's attention to take the time to read your project, article, or message. We'll discuss several common abstract formats for geospatial analysis writing.

Now... don't wait for final feedback from the instructor--begin your data gathering now!