Strategic Consulting Agency. Fort Lauderdale Web Design, Branding, Digital Ad Marketing Agency, CRM Software

The first thing most people look at when landing on a web page is the headline. If the headline captures their interest, they will be drawn into the content of the rest of the page.

Headline Rule Number 1 — Offer Solutions

The headline of your web page is your first opportunity to begin this process. It needs to offer reassurance to the page visitor that you have what they are looking for. In other words, it needs to offer a solution to whatever problem they are experiencing.

With your headline, you only get one brief moment to get your message across and make a great impression. So there’s no time to beat around the bush. Instead, tell the page visitor exactly what they want to hear.

For example, let’s say you are promoting digital products in the dating and relationships niche for guys looking to learn how to meet more girls.

At Last: “Get Any Girl’s Number in Just Minutes Using this Groundbreaking, Can’t Miss Technique That Works Like Magic!”

This type of compelling headline grabs the visitors’ attention and lets them know you have the solution they are looking for.

How to Create Headlines that Will Attract Click-Throughs – Headline Rule Number 2 — Use Action Words That Build Excitement

If you want the page visitor to continue reading your web page content, use action words that actually push them into continuing.

In the above example, the phrase “At Last” is a way of telegraphing that something unique is coming next and the phrase “Get Any Girl’s Number” uses desire (or the promise of sex) to push the reader into reading the rest of the copy.

Finally, the phrases “Can’t Miss Technique” and “Works Like Magic” build excitement and make them want to learn more.

How to Create Headlines that Will Attract Click-Throughs – Headline Rule Number 3 —  Be a Tease

An effective headline offers solutions, builds excitement, and uses action words to capture the reader’s attention, but it doesn’t always have to just come out and say exactly what it is that you are promoting. Using the same example from above, what if the headline for the same product read:

“Want to Know One Weird Trick that Will Help You Meet More Girls?!”

It informs and promises a solution, but it also captures the interest and imagination of the reader. Teasing the reader without revealing everything in the headline makes them want to keep moving on to your content to find out more.

Have you ever had a file cabinet that you kept shoving papers into until it was too full to close?

Digital data overruns work the same way. In both instances, the overflow doesn’t occur overnight, although it can often seem that way.

Managing Digital  Too Much Information

Data growth happens gradually over time until one day somebody discovers it and has to deal with it. This is how big data actually happened. Company files and databases were manageable at first, but then kept getting bigger and bigger. But it wasn’t until recently that companies purposely sought to grow data, making the problem even worse.

In reality, data analysis has been happening all along. Companies had tools to analyze data – such as database administrators, math geniuses, code writers, statisticians and functional algorithms. But at some point the sheer volume of data simply became too big to fit into data center storage.

Break It Down into Manageable Pieces

In response, some companies began running an analysis on select data samples, rather than the full set. This sometimes worked, but most people agreed it wasn’t the answer. When big data tools were developed, they were welcomed with open arms as a cheap and effective way to analyze huge amounts of data. Now companies are looking for ways to make big data tools cheaper, faster, more efficient and easier to use.

Real-time analytics is one of the most widely hailed advances of our time. It provides on-the-fly analysis of large data sets for the first time, so companies can see exactly what is going on right now and respond accordingly in real time.

But like all tech applications, real-time analytics isn’t a cure-all. There are times when they shouldn’t be used. The answer to when they should be used needs to be made on an individual basis based on an organization’s specific overall strategy, market, and customers.

Big data is changing the economy as much as it is changing business, ushering in a new data economy in which data can be exchanged for money or used in place of money. Data is quickly becoming a valued resource and a bankable asset.

Yet most businesses don’t post data on their profit and loss sheets and don’t report it as an asset to be depreciated to the IRS. Nor can companies borrow against the value of their data.

So how can data be an asset when it doesn’t look or feel like other real assets?

Data Is Knowledge and Knowledge is an Asset

It’s helpful to think of data as knowledge, which is something that can be bought, sold and traded. For example, when you graduated from college, you had knowledge. You could use this knowledge to get a job.

The company that hired you bought your knowledge by hiring you. Even if you didn’t get a degree, you can gain knowledge from experience then use that to get a job. So knowledge is an asset for both employers and employees.

Does Your Business Collect Big Data – Monetizing Your Data

Yet it’s not something that can be listed on a P&L as a taxable and depreciable asset or used as collateral for a loan.

Why not? Because it’s nearly impossible to assign a value to knowledge because there are too many unknown variables. Two college graduates might have the same degree, but they generally won’t perform exactly the same in the same position. Nor will two people with the same amount of experience perform the same.

So a specific value can’t be assigned because there isn’t an easy way to objectively measure the amount and usefulness of an individual’s knowledge or how they will use it in future situations.

Does Your Business Collect Big Data – Data as an Asset

The same holds true for data – a type of knowledge – that a company owns. Few companies have mapped their data holdings, let alone their applications and future market value.

Yet without this type of clearly defined measurements, it’s almost impossible to assign a true value to data. Instead, data has to be considered a strategic asset rather than a hard asset.