Posts Tagged ‘ Payday Leads ’

3 Reasons Why “Big Data” Isn’t Really All THAT Big

Quality Payday Leads

Over the last couple of years, Big Data has been unavoidable. It’s not just big, it’s massive. If you throw a stone down the streets of London or New York, you’ve got as much a chance of hitting a big data guru as you do a social media guru.

Undoubtedly, there is great power in data, but is Big Data all it’s cracked up to be?

50% of my brain thinks Big Data is great, and 50% of me thinks it’s a neologism. I’ve found it difficult to reconcile all of the varying information out there about it.

So join me for the first part of a two-part series looking at Big Data. In part one, I’ll look at Three reasons why Big Data is a big load of baloney. And next week in part two, I’ll look at Three reasons why Big Data is awesome.

1. Big trends are trendy

My pet rock still hasn’t moved, and my Tickle-Me-Elmo still won’t shut up. And also, Big Data is big, at least according to Google Trends:

Targeted Data

Some other terms once synonymous with the inter-web were pretty trendy too. Remember this one?

Auto Finance Leads

The adoption curve of the term “web 2.0” looks quite similar to where we are now with Big Data. And yet, if you still use the term “web 2.0” in your job, then you probably think the Fresh Prince still lives in West Philadelphia. (He doesn’t.)

The thing about Big Data is that it really isn’t anything new. Cluster analyses, propensity modelling, neural networks and the like have been in use in the marketing sphere for quite some time.

The phrase used a few years ago for this sort of stuff was ‘business intelligence’


But now, we don’t care about business intelligence anymore. Who needs intelligence? It’s over-rated. Like Goethe said, “All intelligent thoughts have already been thought”.

And yet, Big Data is everywhere. Why shouldn’t it be? It’s BIG. However, you ask 10 people what Big Data means, you’ll get 10 answers, none of which make much sense.

Maybe it’s because of this:


We’ve all seen Moneyball and read Nate Silver’s blog. There are people out there who are better at statistics than you. And this is scary.

So what’s the solution? Throw a bunch of money at Big Data, whatever it is, and sleep soundly knowing that you’ve gainfully employed a math graduate.

And therefore, Big Data is a big load of baloney.

2. Missing one V

Gartner defines Big Data as requiring Three V’s: Volume, Velocity, and Variety. So let’s look at this a bit deeper.

Volume of data: for sure, there’s loads of data out there. Huge amounts. Check.

Velocity of data: yep, data is moved around in large quantities faster than ever before. Check.

Variety of data: in most digital marketing ecosystems, there are the following types of data (yes, I know there are more, but for the sake of argument bear with me):

  • Site stats.
  • Email engagement stats.
  • Mobile/SMS stats.
  • Past purchases.
  • Demographics, preferences etc.

And within each of these, the options are finite. For example, in email, most people measure (at the very least) opens, clicks and conversions. That’s three types of data.

And for all of the other areas above it’s the same. For the sake of argument, let’s say that we’ve got 30 types of data in total.

This is the thing. 30 types of structured data. Processing this data doesn’t require a super-computer, it simply requires robust statistical methodology.

So, if you’re a digital marketer, what you actually have is ‘a few sets of structured, small data’, not ‘Big Data’.

And therefore, Big Data is a big load of baloney.

3. You can perfectly predict the past

With the beginning of the National Hockey League’s 2013-14 season fast approaching, I’ve been spending a lot of time lately trying to determine the best bets to place on the eventual winner.

And of course, it seems Big Data is the best route to my next million dollars. (Btw if anyone is interested in joining my hockey pool then drop me a line – go-live is 1st October!)

I downloaded as many team statistics as I could from last season and embedded them into a spreadsheet. It included rudimentary statistics such as Goals For and Goals Against, right through to Winning % when trailing after two periods, CORSI 5v5, and defensive zone exit rate.

Then I ran a multiple regression and removed non-causal variables. I perfected the model such that the formula spat out expected point totals that were on average within 0.5 points of the actual result.

When I plugged in the raw data from the previous season, the outputted expected results weren’t even close to the actual results.

This is a perfect case of what is called ‘over-fitting’.

When you have a lot of data, the urge is to use all of it and create an uber-complex, bullet-proof formula. Take all of your data points and find the trendline that touches everything. But there’s an inherent problem with this – all you’ve done is create a formula to perfectly predict the past.

The risks that come with an over-fitted model are twofold:

  1. You are assuming that the future will      be the same as the past.
  2. Adding or removing variables becomes      extremely difficult and risky.

So despite there being lots of data out there, the dominant strategy is to focus on the causal variables. In the hockey allegory above, while I won’t reveal my secrets, two of the stronger predictors of eventual success are goal differential and shot differential.

Not rocket science, I know – if you take more shots than your opponents you’ll generally score more goals than your opponents. However, I did learn to remove strictly correlative variables (such as Faceoff Win %, PDO and punches thrown).

Instead of focusing on Big Data and its billions of variables, I’m instead focusing on a small amount of variables that actually matter.

Within your organisation, what are your causal variables? By looking at all the Big Data available to you, you run the risk of the truly valuable signals being obfuscated by irrelevant correlates.

And therefore, Big Data is a big load of baloney.


I do too. Well, 50% of me does. Feel free to elaborate on your point of view in the comments section below.

Parry Malm is Account Director at Adestra and a guest blogger on Econsultancy. Connect with him on LinkedIn or Google+.

Topics:Data & Analytics

by caesararum

WWW.APEXDM.NET  “Your Turnkey Solution to Leads & Data”


Payday Collection Deception



On classic episodes of the Tonight Show, affable sidekick Ed McMahon sought guidance from Johnny Carson’s all-knowing Carnac character. But as demonstrated by a recent FTC law enforcement action — which involved a company’s misleading reference to the late Mr. McMahon — you don’t need a psychic to know that challenging deceptive debt collection practices remains a top priority.

According to the complaint, defendants Luebke Baker & Associates, CEO Kevin Luebke, and other corporate managers used illegal tactics to collect a variety of debts, including magazine subscription debts, many of which they knew or should have known weren’t valid. Some of the magazine debts traced back more than a decade to a company the FTC had successfully sued for deceptive marketing. Despite the fact that the defendants had been notified of a 2003 federal court order that placed special restrictions on anyone attempting to collect payments related to that seller, the FTC alleged the defendants ignored those requirements and repeatedly told people the debts were due and payable.

The defendants’ “rebuttal sheet” — attached as an exhibit  to the FTC’s court papers — offers insights into just how far the defendants went to try to collect debts. For example, when people refused to pay, the defendants directed their representatives to illegally threaten to contact their employers: “I am trying to help you out. I definitely don’t want be the bad guy but our client sent over your employment information and I would like to handle this with you on a voluntary basis before we have to get your employer involved. Blah blah if getting nowhere.”

If the consumer still balked at paying, the defendants read off the person’s work address and threatened to get law enforcers involved: “A sheriff will deliver a summons to either your place of employment or your home. It depends on what we instruct the peace officer.”

If people exercised their right to ask for documentation for the alleged debt, the defendants really turned up the heat: “Typically when someone requests proof and it’s clear to us that this is their bill, you may possibly receive your requested credit card itemization stapled to a summons to appear in court.” In addition, the FTC says they falsely told people that magazine subscription debts are exempt from the statute of limitations and illegally threatened to garnish wages and take other actions with no intention of following through.

So how did Ed McMahon’s name enter into the story? According to the FTC, the defendants tried to hide their identity by sending untruthful Caller ID information — for example, by falsely posing as prize pitchman McMahon.

But the illegalities didn’t end there. The FTC says that in addition to violating the Fair Debt Collection Practices Act and Section 5 of the FTC Act, the defendants marketed a “credit repair” CD in violation of the Telemarketing Sale Rule, which makes it illegal for companies to charge up-front fees for credit repair goods and services. (Note to self: A debt collection outfit charged with FDCPA violation? Perhaps not the best source for information about “repairing” credit.)

The defendants entered into a settlement  that bans illegal tactics in the future. The order doesn’t just apply to the corporate defendant and the CEO. Also named individually are the Director of Operations, the General Manager, and a Collection Manager. In addition, the settlement imposes monetary judgments against the defendants totaling $3.1 million — including a $420,000 judgment against Kevin Luebke’s wife, Julissa Luebke. Most of the judgments are suspended due to the defendants’ inability to pay, but if it’s later determined they gave false financial information, the full amount will become due.

Two message for debt collectors. First, the law draws clear lines between lawful practices and illegal tactics — and debt-related abuses remain a top enforcement priority. Second, should you conclude that even with an “Inc.” after a company’s name, defendants may be held individually liable for law violations? In the words of Mr. McMahon, “You are correct, sir!”

By Lesley Fair

S. Tyler Stapley
Apex Direct Marketing – CEO / Owner
Office- 714.203.7577

Cell – 714.717.9303
E-mail –
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“The harder I work, the luckier I get.”
Samuel Goldwyn


Payday Loans Becoming More Popular With Middle-Income Earners


As many middle-income earners struggle financially, payday loans are becoming a more popular source of money. Are they though the best option for a short term loan?

With prices on the rise across many staple household needs, including gas and electricity, petrol and food, many families face falling into debt as they struggle to keep up with their outgoing payments.

And it’s not just low-income families who are struggling, it’s middle-income families too. According to This is Money, around 57% of payday loans provider Instant Loans Direct customers, are people earning between $35,000 and $65,000 above the national average wage.


With credit cards maxed out, credit rating unattractive to lenders, payday loans can appear attractive as a short term loan. After all, for what seems a small amount of money you can borrow a few hundred dollars for a few days – that’s what they’re designed for, to get you out of a hole until payday comes.

Few credit checks are made and you can get the money into your bank account very quickly.

The issue is, for this convenient access to money, interest rates are very high, and can be equivalent to over 1,000 per cent.


If a loan is not repaid in the agreed time, the charges can be significant and you can easily find yourself with further debt that you have little chance of being able to repay.

The payday loans industry is already worth over $1 billion and growing rapidly as more and more people need quick loans and are either denied access to or are not prepared to approach conventional lenders, such as banks and building societies.


MoneyHighStreet comments: “When your salary runs out before the end of the month and yet you still have bills to pay, turning to a short term loan to ‘tide you over’ will be a welcome option for many.

The issue is though unless you address the underlying problem of your outgoings exceeding your income, you will find yourself in the very same position next month. In fact it’s likely to be worse in that you’ve added to your outgoings by the cost of your short term loan.


So can you set a budget so that your income exceeds or at least equals your outgoings? Can you save money anywhere?


If not, or you can’t totally balance your money, is there another option you can use for a short term loan? For example do you have any assets, such as a car, watch, jewelery or perhaps some art, that you can use to secure a loan?


In this way you are making your assets work for you. Of course you still need to pay the cost of the loan but in a worst case scenario you can sell your assets to cover the loan – or rather more positively get your assets back once you have improved your financial position with your better money management and sticking to your budget.


Another option may be to turn to family for a loan. Many are seeing this as an easier option and in certain circumstances it can work well.


If you are facing mounting debt though that you have no chance of clearing, even if you manage to get a loan for a period, you really need to tackle the route problem sooner rather than later – debt will not go away on its own, you need to take steps to clear it, getting advice from a professional organization.