Play to your strengths or mitigate your weaknesses?

When you’re thinking about business strategy, one of the most basic questions you have to confront is whether to play to your strengths or mitigate your weaknesses.

Playing to your strengths at first seems like the logical answer. Do what you’re best at. Push the envelope. Hit your numbers hard.

By contrast, mitigating weaknesses doesn’t seem like it improves very much in the short term. Sure, you’re less bad at the things you’re bad at, but forward-moving progress isn’t always obvious.

Here’s why both matter. Playing to your strengths is great in the short term, but ultimately your strengths have a limit on them. At a certain point you have growth-limiting factors. This is true in so many areas. It’s true in macroeconomics – structural problems can be masked with economic stimulus for a little while, but eventually stimulus stops working. It’s true in marketing. Your marketing will only succeed as well as the weakest link in the chain; poor customer service or a bad product can nullify even the best marketing program. It’s true even in something as simple as running. The weakest part of you – nutrition, equipment, health, form – ultimately inhibits the strongest part of you.

Those weaknesses create a ceiling that limits your strengths. They cap your growth. Only by removing those weaknesses can your strengths continue to flourish.

This is what it might look like, visualized:

IMG_1429

Here’s the challenge: many weaknesses take a long time to overcome, longer to overcome than playing to your strengths at that moment. The sooner you can start raising the weakness cap, the sooner your strengths can shine to the greatest extent possible.

Ultimately, the answer comes down to balance and careful measurement. Once you start to see the hints of a plateau in your strong metrics, start shifting focus and resources to remediate your weakest metrics.


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Cherry picking your marketing data

Over the holiday weekend, I had a chance to bring a statistics aphorism to life, as I went cherry picking at a local farm. If you’re unfamiliar with the expression, cherry-picking one’s data means selecting only those case studies or data points that reinforce your point, while ignoring the rest. This expression never made a ton of sense to me until I actually went cherry picking.

IMG_9194Believe it or not, half of these cherries aren’t ready to eat.

Here’s why it now makes sense. Cherry trees have a wide, wide spectrum of fruit ripeness. At any given time, on any given tree that is in season, about 5% or so of the cherries will be picture-perfect, ready to pick and eat. About 20% are reasonably close to ripe, but might need a few more days to mature. 5% or so will be past ripeness and on the way to rotten. 10% will inevitably be partially eaten by pests. The remainder will be in various stages of ripening but nowhere near ready to eat.

From a statistical perspective, if you wanted a true understanding of a tree’s ripeness, you’d randomly pick cherries from it and get a wide selection of cherries at various stages of ripeness. If, however, you wanted a more practical, more useful harvest, you’d only pick the ones that were ripe or near ripe, even though your harvest would be statistically non-representative of the tree as a whole.

Cherry picking one’s data isn’t universally bad, however. It’s bad if what you’re after is statistically representative data. It’s good if you only want to look at certain pieces of data. For example, while understanding where your entire marketing database is in terms of readiness to purchase is important, cherry-picking only those prospects who are close to buying or ready to buy makes logical sense from a resource management perspective. You want your sales and marketing efforts to focus first on those opportunities that are most ripe before they cross into overripe (and likely buy from someone else).

Understanding what your end goal is – statistically valid representation or the best of the best – will help you to understand whether cherry-picking your data is a bad or good choice.


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8 easy steps to finding returning visitors in Google Analytics

One of the most important metrics in web analytics is the number of returning visitors to your site. This simple number tells you just how well your site is really doing; after all, it’s easy to get someone to visit your site once. You can run ads, engage on social media, run a great PR campaign etc. It’s harder to get them to come back – for that to happen, you have to be providing some reason for them to want to return. Your content has to be compelling, your site has to be navigable, your value must be strong enough to make a visitor choose you over something else they could be reading.

Yet in most web analytics packages, this simple number is hidden away. Here’s how to find it in Google Analytics, the most popular web analytics package.

First, go to your Audience menu [1]. Then choose New Segment from the Segment Navigator [2]:

Audience_Overview_-_Google_Analytics

Next, choose System segments [3] and uncheck All Sessions [4]:

Audience_Overview_-_Google_Analytics

Scroll down until you find Returning Users [5]. Click it to turn it on, then click the blue Apply button [6]:

Audience_Overview_-_Google_Analytics

Now for clarity’s sake, adjust the date to be the last 3 months or so [7] and change the view to weekly so that it smoothes out the graph enough to see a trend [8]:

Audience_Overview_-_Google_Analytics

With these 8 steps, you should now see whether your site is working better or worse for you:

Audience_Overview_-_Google_Analytics

If the line isn’t going up and to the right, you have a retention problem. You have a stickiness problem. You may have a navigation or content quality problem. Once you know this, once you know whether your site is getting people to come back or not, you can begin testing and deeper analysis to determine why your site isn’t working.

If the line is going up and to the right, then you can dig deeper into your analytics to find out why. You can look at things like bounce rates, time on page, which pages are most popular, etc. and play to their strengths.

Try this out and see how sticky your site is!


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