Looking for Edmonton small business accountants? Well, we can happily recommend one of our Greenhouse Program clients, Origami Accounting. The firm provides complete small business accounting and bookkeeping services for a flat monthly fee. The Origami team has a laser focus on the needs of small business owners, and they’re doing some new and interesting things in a very traditional field. Definitely worth a look.

Small business owners have some interesting choices to make when Groupon (or one of its many clones) calls. Here are some useful articles, blog posts, and research papers to help you think through the decision of whether to do a deal and, if so, what type of deal to choose.

A small business has two locations: its address and its positioning. An address tells customers where to find a business in the real world. Positioning, meanwhile, is a marketing concept: it’s (roughly) the location of a business in a customer’s mind relative to its competitors.

Positioning in a nutshell

Positioning was popularized by Al Ries and Jack Trout in their 1981 bestseller Positioning: The Battle for Your Mind. Their premise is that in an over-communicated world, consumers screen and reject much of the information being offered and only accept whatever matches their prior knowledge or experience.

Businesses have to adapt to this environment by oversimplifying their message and by concentrating on narrow targets, the consumer segments that are most likely to listen and respond to their marketing. By focusing, businesses can hope to find some unoccupied space in a target consumer’s set of perceptions and set up shop, if you will, at a safe distance from competitors.

80% of your sales come from 20% of your customers. As a small business owner, even if you’ve never heard of the Pareto Principle, you know this rule of thumb intuitively. You’re in business largely because of the support of a fraction of your customer base: your best customers.

From a marketing perspective, it makes sense to put in the effort to understand the characteristics and preferences of your best customers for at least two reasons: 1) to continue to provide this group with what they’re looking for and keep them as customers, and 2) to target your marketing efforts toward prospects who resemble your best customers.

By targeting your acquisition marketing through insights into your best customers, you attract customers who are likely to respond to the strengths of your small business and remain loyal to it. Instead of moving random customers up loyalty ladders, you focus instead on getting the right customers, customers who will be loyal from the start.

But, before you can start to understand your best customers, you first need to identify them. And that’s where a simple database marketing tool called recency, frequency, monetary analysis (or RFM) comes in handy.

Google Edmonton marketing companies. On the first page, you’ll see two actual marketing companies in Edmonton. Who’s keeping them company? Job listings, directories, a web design company, a technology blog, and an Internet marketing (read SEO) expert. Not enough to help you understand the Edmonton marketing scene.

I have two objectives for this post: 1) provide a more useful list of Edmonton marketing companies; and by using very simple on-page SEO techniques, 2) try to get ranked for searches on marketing companies in Edmonton. If you found this page on Google and it helps you find a local marketing company that fits your needs, that means I’ve succeeded in both the first objective (building a useful list), and in the second (giving Google the type of content it likes). So, let’s get listing!

TweetHeroes is a Twitter app that discovers and ranks influential users tweeting on specific topics. We built it to make sense of the conversations, players, and networks in Twitter. We know about wefollow, Klout, twitaholic, and Twitalyzer among others. They just didn’t show us what we wanted to see or how we wanted to see it. So we built our own social media analytics thingy. Here are three ways you can use it.

Want to know the central players in networks that are tweeting about Boston, Seattle, Ottawa or 30 other North American cities? How about political networks like the Tea Party or Gov 2.0? Check out our topic-specific ranking pages like this one for New York City:

Over the past couple of months, our team has been working on TweetHeroes — a Twitter tool to discover and rank influential users on specific topics (among other things).  During this time I’ve followed the #yeg stream, let’s say obsessively.  And I’ve noticed that the debate over the Edmonton City Centre Airport (#ecca) is pretty much a constant, consistently trending among the influential #yeg users.

There are two sides to the debate: support the plebiscite or dead issue, move on.  So where does everyone stand?

Good question.  Because our team is conditioned to see everything in terms of networks, we decided to dig into the #yeg #ecca stream over the past couple of months to see how the players in this tempest are connected.  We identified #yeg Twitter users who’ve tweeted at least twice about #ecca and #yeg in that roughly two-month time frame.  We then built the retweet network for these users, connecting two users if either one has retweeted the other. (Twitter retweets on issue-specific tags are excellent indicators of affinity or a shared position.)

At this point, we had a confusing and densely connected graph — the #ecca tag is very popular! What we really wanted to know though was where everyone stood, not just on the issue, but in relation to each other. Who was on each side? Who was central? Who was supporting whom?

We know from last week’s post on analyzing the Edmonton census data that adjacent age groups generally tend to group together in Edmonton neighbourhoods; e.g., 50-54 year-olds tend to live in neighbourhoods with relatively higher numbers of 40-49 and 55-59 year-olds. I’m going to take this idea a little further and, using some common clustering techniques, show how Edmonton neighbourhoods can be divided into 5 major age-based clusters.

Clustering in a nutshell

According to the Wikipedia article, clustering is “the assignment of a set of observations into subsets (called clusters) so that observations in the same cluster are similar in some sense.” The most famous clustering algorithm, and the one that we used for this analysis, is called k-means. (Andrew Moore has an excellent tutorial for those interested.) K-means is a relatively simple but powerful technique that’s very useful for exploring datasets. There are quite a few details that a practitioner has to sort out (e.g., scaling, collinearity, etc.), but the output of k-means often reveals clear and distinct patterns and helps us get our bearings, particularly with marketing data.