The DigMyData Blog

What Radio Shack Can Teach Us About Online Business Success

Posted on July 27th, 2011 by admin in Blog Short Story Thoughts


Yeah... this is where I spent a lot of time as a child.

For most of the time when I was a child, my dad worked at Radio Shack — first as a computer specialist and then a store manager. Getting access to TRS-80 computer technology at such a young age and being able to self teach myself computer science (look ma — I’m referenced in ACM) was directly attributable to my father’s career there. Retail store lingo and thinking was a part of every day life. More importantly, his retail sales success meant the difference between public school and private school (at least before high school). It meant the difference between the car breaking down being a stressful financial disaster or a minor inconvenience.

A Radio Shack store manager back in the day was compensated 3 ways:
- A base salary (paltry)
- Commission of sales (just like the sales people working for the manager)
- A bonus based on how the store performed versus last year

The bonus could be significant — Radio Shack was aggressive back then and wanted to incentivize growth. The savvy store manager quickly learned that focusing on overall store performance — instead of personal performance — was the most lucrative path.  My father was savvy and become adept at optimizing a Radio Shack store and turning it into a sales engine.

These were the variables he had to work with:
- Traffic — the number of people coming into the store
- Sales Tickets per Visitor — how many sales occurred per visitor to the store
- Average $ per Ticket — the average dollar amount per sale
- $ Returned — how much merchandise was returned to the store*

*This was always frustrating in that even if someone bought an item at a different Radio Shack, the return still counted against my dad’s store. Some Radio Shack managers refused to refund large purchases and send them to other stores (a big “no no” and a huge matter of contention between different store managers).

The formula then became easy:

Traffic * (Sales Tickets per Visitor) * (Average $ per Ticket) - ($ Returned)

That was it. That’s what he had to optimize. This was the formula that meant the difference between “barely hanging on” and “doing ok.”

Each of these things would be addressed sequentially. Traffic could be manipulated through merchandising and keeping the store looking spiffy. Sales Tickets per Visitor could be improved through classic sales techniques (greet the customer, sell the product, ask for the sale). Average $ per Ticket could be increased through upsells (accessories, batteries, cables). $ Returned could be minimized by managing buyer’s remorse — making sure that the sales process appealed to the customer both emotionally AND logically.

When you are running an online business, whether you sell Software as a Service (SaaS), physical goods, or virtual goods, this is just about all you have to work with as well. It’s so easy to get sucked into multivariate testing, new product features, or social media that we forget that, basically, we’re just running an online store.

DigMyData is about optimizing your store.

Traffic. Sales. Support.
Traffic. Sales. Support.

This is what drives your business. You must stay on top of these. You have to know immediately if one of these starts to act funny. You have to know which one of these to focus on right now.

You’ve probably seen my MacBook2TV.com demo business in our product screencast. The success I’ve had with that really is because of DigMyData.

Houston, we’ve got a problem

DigMyData is what made it obvious to stop focusing on paid traffic and to focus on organic traffic.

Paid Traffic Is Expensive

A way out

DigMyData is what made it obvious that my organic traffic efforts were working and that it was time to focus on sales conversion rate.

I'm #1! I'm #1!

DigMyData let me know that Google was sending me loads of new traffic and that it was time to tweak the website to make sense for the new keywords people were searching for.

Google is laughing maniacally and ranking me for "Mediterranean Cruises for Dogs"

DigMyData tells me that my support costs are under control.

Support E-Mails Look Good (except for that 1 guy)

DigMyData keeps my eyes focused on the prize — an online store that makes money.

Money. It's what I want.

Conclusion

Online business success is not mysterious. It obeys the same sales laws that the traditional brick and mortar stores discovered through centuries. It does require hard work. It does require focused attention. DigMyData lets you focus on those important variables that are at the heart of your formula. It makes the work a bit easier.

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New Release: MailChimp + Story Points

Posted on July 22nd, 2011 by Adam in Blog Development Marketing Starting Up
Over the 4th of July, as the fireworks were dying off here on the east coast, we updated DigMyData with two features we’re really excited about launching: MailChimp integration and Story Points.

Story Points

We will be detailing more about how to use Story Points to put important events in the chart to help explain why things are the way they are. Funny story about Story Points. We were talking to someone with early access (more invites coming soon!) and they asked how they could “write on the chart”. When asked what they had in mind he said, “You know – like on your website. How do I do that?” We knew we wanted to do some type of chart annotation, but because of that feedback and because Ryan Carson thought it was an effective design (at least for the homepage) we decided to just roll with that basic approach. We think it works very nicely.

Story Points are how you can capture data (ex: offline events like when you spoke at a conference or put in a placeholder for an unexpected dip). Mark and I have begun to label our own DigMyData chart at the places where lines jump up/down and with why it happened (or at least why we think it happened). Story Points we have included in our chart are: explanations for traffic jumps, new feature releases, and our sponsorship of LessConf. All together, these points begin to form a story where the real data from your business gets curated into a timeline of lessons learned.

Add a story point to a line (ex: website launch, offline marketing, policy change)
Story Points are added to a point on a line.

Bonus: Add a story point to a date in the future to test your theories.

MailChimp

The email marketing darling MailChimp has been the follow up question for easily half of our early access users: “When will MailChimp be an option?” The standard answer it seemed was always “2 weeks out” (such is the life of a bootstrapped startup). Fortunately, we’re not getting those emails anymore as our most recent update included support for MailChimp.

MailChimp is great because so many of you out there use them to communicate with your customers to keep them informed and to drive sales. Setup is very easy; we link to a page in MailChimp, you create a key, and then paste that key in your DigMyData settings. All that is left is to select which campaign to import.

Introduction to MailChimp:

View subscribers over time + campaign events

Google AdWords integration
In our last week we included Google AdWords for the first time. There were a few issues that made the feature not quite as reliable as we prefer.

View ad cost and number of paid visitors

As always, you can reach us at support@digmydata.com or on Twitter: @digmydata Links: login or signup

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New Release: Forecasting

Posted on June 15th, 2011 by Adam in Blog Development Starting Up

In Back to the Future II, Biff Tannen grabs a sports almanac from 2015 (yes, 2015!) and returns to 1955 armed with scores that make the 1955 Biff very rich. As of Tuesday, DigMyData users can see see the future as well – though we can’t promise you the riches Biff saw, we’re pretty sure forecasting will help you run your business.

Forecasting

What we are doing right is pretty basic modeling that takes about 90 days worth of your data and projects it out in linear fashion with a bit of weighting to make more recent data move the line up or down a bit more. We recognize this is a simplistic method – but we feel that it is a great start.

In the future, we’ll look at a more robust model looking at annual, monthly, weekly patterns (we’d really like to look at day of the week and last day of the month assumptions and any correlations with holidays or other specific events). This will be an ongoing process and over time we will make this an even more helpful tool.

Why

We put forecasting into the product because you can’t change anything about the past. Doc Brown’s DeLorean can’t take us into the past and fix something – all we can do is learn from it. The future, on the other hand, is full of opportunity. What we do today CAN change what happens tomorrow.

This changes DigMyData completely – rather than only looking backwards, forecasting out what your business will look like in September – or the end of the year or even in 2015 – helps you think about where you want to be. The forecasts will challenge your assumptions about where you think you will be on those dates.

Some examples:

Sales -

You’ve been telling your spouse that you will quit your job as soon as the company is bringing in $3,000 a month. Now you know when to put in your two weeks notice.

You want to hire a full-times salesperson once you reach $10,000 in monthly sales. Forecasting, even our simple method, will give you a good idea when you need to start asking for referrals.

Support -

You know from your calculation lines that you get X emails for every sale you make. You’re happy to talk to your customers, but at some point you’ll need to hire someone, even part-time, to help interact with your customers. Don’t be surprised – just look into the future.

 

How to use Forecasting

We do our very best to not make new settings for every new feature we release. We work hard so that the defaults will just work for most of you. In this case, we have turned on forecasting for all customers for all lines. Just drag the chart to the left or press the arrow key –> to move the chart into the future. You’ll notice that the current period (shown below) has a solid line on the left and a dashed line on the right.

We show the current period point in the forecast position which gave us a distinct advantage over our previous UI (and just about anyone out there): No more cliff (line) dives!

Previously, when you reached today, this week, or this month, the line would dive to zero since the data was incomplete. No longer!

 

 

Go to it!


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