Category Archives: Data

All about cleaning, updating and using data.

Numbers Can Lie

Did you ever play “Telephone” when you were little?  Remember what happened to that whispered message passed through 10 kids and how easily “Strawberry Jam” turned into “I am a banana”? It was funny then.

Research findings, passed via content marketing and social media are a lot like “Telephone” because once a number is repeated often enough, small changes in the interpretation can create a very different story. Even worse, every time something is repeated, it takes on a greater authority – even if it’s questionable to begin with.

Here is a finding from the CEB, MLC Customer Purchase Research Survey, 2011 which is quoted extensively by subject matter experts and in other reports including “The Digital Evolution in B2B Marketing” among others.

It states that:

On average, customers progress nearly 60% of the way through the purchase decision- making process before engaging a sales rep.

This finding – fine tuned in an included chart in the report to show that almost 60 is actually 57% has surfaced, over and over and over in countless discussions and B2B studies. An additional comment about the response distribution indicates an upper limit of 70% so that number shows up quite frequently as well.

  • 57% being close to 60% is frequently represented as two thirds- once it hits 2/3’s  well, that’s  “almost 70%”
  • 70% – well that’s pretty darned close to three quarters, which is almost 80%

I’ve seen all of these numbers passed on as absolute fact.  I’ve also seen it written as 2/3-3/4  of companies have made the decision before calling in the vendor. (Just a little slant on the interpretation – It’s a “Telephone” thing)

But even the original number isn’t telling the whole truth.

In a direct quote from the Digital Evolution in B2B Marketing, about how this number came to be it states:

” To understand the scope of this issue in the B2B context, CEB’s Marketing Leadership Council (MLC) surveyed more than 1,500 customer contacts (decision makers and influencers in a recent major business purchase) for 22 large B2B organizations (spanning all major NAICS categories and 10 industries)….”

1500 contacts involved in a recent major business purchase sounds pretty impressive, but 22 companies?   What that means is the “recent major business purchase” involved an average of 68 decision makers and influencers. (1500/22=68.18)  A distribution chart in the original report clarifies that yes, indeed we are talking about only 22 companies, or a total of 22 purchases.

For 22 major purchases, each involving an average of 68 decision makers and influencers (and I’ll stick my neck out here to also suggest literally millions of dollars) the customers delayed engaging with sales reps until they were 57% through the process. I wouldn’t be at all surprised if the first 50% of the process was about figuring out what each of the obviously many involved departments required- not to mention whose budget would be taking the hit. It’s hardly what I would describe as a “striking finding” – more like a bit of a snore. But look at the fuss that number has caused.

So, for most the the B2B vendors out there who are wondering what to do with your apparently antiquated sales team, may I suggest – “Turn them loose.”

Think of it like this – Does 68 decision makers and millions of dollars look like a representative B2B sale?

More to the point – does it look like one of yours?

Website Leads and Your Inside Sales Team

How quickly do your inside sales team follow up on web leads?  I’ll bet that the answer is “Not fast enough”.  According to the B2B Buyer Behavior Report, from Software Advice your chance of qualifying a lead is 29% better if you call within 5 seconds rather than lounging around for 5 minutes before making the call.

Check out some of the other interesting findings in this research:

5 Problems that are Killing Your Results

This is about hidden or ignored problems that are killing your results..

Why is our campaign failing?

There are lots of reasons why a marketing campaign can fail to deliver the intended responses from a business audience. But over the last ten years, working with B2B companies on literally hundreds of event registration, lead generation and sales support programs, I’ve found that there are some incredibly easily resolved mistakes that continue to dominate the  “Duh.Whatever were we thinking?” list.

What makes these mistakes stand out? A few things.

  • They are brutally common.
  • Most clients are aware of these problems but underestimate the impact.
  • They’re easy to make and relatively easy to fix.
  • One of them stands out because it totally blindsided everyone.

So, here are links to 5 posts that talk about things that can easily be sitting in the background and killing your marketing efforts.

  1. Ignoring Bad Data is Very Expensive
  2. Your Premium Can Turn into a Nightmare
  3. Forgetting that Beauty is in the Eye of the Beholder
  4. Sales Reps are Not Making The Calls For You
  5. Your Campaign is Running for Too Long

Exactly How Bad is Your Data?

Underestimating the damage caused by an out of date and duplicate riddled database is the most frequently made and damaging mistake.   If I had ten bucks for every time I’ve heard a client admit that their database is lousy, I probably wouldn’t quite be able to retire yet, but I’d sure have a lot more money than I do right now.

When I ask the question -“Just how bad is it? ” the average answer is that about 10-20% of the records are probably out of date and the reason it can’t be fixed is that there just isn’t the time, the money or the directive from senior management to do the clean up.  I can only guess that they have decided  the data is better than it really is and that it’s not important enough to worry about. That really needs to change.

Databases require constant, relentless maintenance. A database is – in my occasionally humble opinion, the greatest example of entropy that exists in the modern business universe. A database is constantly degrading. It doesn’t take a vacation from falling apart and it becomes virtually useless long before it reaches the point where it can’t get any worse.

A database is an asset which when left alone turns into a liability.  Would you tolerate a furnace or air conditioner in your home that only ever delivered half of what you were paying for? Would you put up with a car that only EVER got you half way home or an elevator in your office that never made it up to your floor?  Then what is the logic of taking something as vital to your business as your customer and prospect universe and ignore the fact that 20% of the records are no good?

You really have no idea just how bad it is.  That 10-20% out of date is probably a lot worse.  It’s probably more like 30-40% out of date and even that wouldn’t be quite so disastrous if you could tag and isolate which records are no good, but even that hasn’t happened in many cases.

Your sales team is NOT cleaning and updating your database as they make their calls. How can anyone actually expect that their sales team is cleaning up the database? Really.  I don’t understand if this is a case of completely underestimating the true value of sales time, if its just a pathetic excuse for ignoring the problem or its something that actually might apply to companies who do not have a real sales team, just a bunch of telephone order takers who are perfectly suited to take the role of overpaid inaccurate data entry staff. But if you have a real sales team, making real sales calls, with real sales quotas you expect to be achieved, don’t believe for a split second that they are expending one minute of precious time updating the database. It’s not happening.

So what is it costing you?  The short answer is a larger small fortune that you might think. Your marketing team is working with budgets that will often limit the number of contacts messaged with any given type of campaign. Simplistically, you could say that if 30% of your data is our of date, you’re throwing away 30% of every campaign investment, but it’s not quite that simple. Since contacts are usually pulled based on different criteria  the bad records will be scattered randomly throughout any list. No two will be the same, which means that there is no way to provide a consistent value for either the built in wasted money or the response failures due to bad data.

That means you can’t even accurately measure your responses. So you cannot test or at some point improve ANYTHING.  You cannot measure your creative, you can’t evaluate your offers, you can’t accurately benchmark a single metric.

Your marketing team looks incompetent because your response levels are always going to be lower than they should be (or really are) and you can’t improve them through any mechanism beyond dumb luck.  You will throw away bad ideas without ever understanding why they’re bad and you’ll throw away brilliant ideas because you never figured out they’re any good. One  of the most important tasks a CMO faces is to deliver a measurable and improving ROI on marketing investment and demonstrate a contribution to revenue and the bottom line.  Just how bad do you look as a CMO when everything your measured on is based on immeasurable data?

No one using your database will care about entering more junky information which gives your sales reps the prefect excuse not to keep their notes for client information up to date and will probably mean that not only will your customers not receive any new sales or marketing information, they’ll also miss your administrative updates.

Licensing and maintenance renewals will be lost or late and your A/R results will be similarly affected. If you add up all the ways that your company can lose revenue opportunities and incur unnecessary expenses all because of databases that are out of date.

There are many companies offering software and services that will allow you to evaluate your data and some fixes are more easily secured than others, like address, telephone and email information.

Other, potentially more important updates like finding the correct contact names might require a more individual form of intervention like the Boxpilot’s Data Filler Service





Clean Data is Everyone’s Responsibility

Too many businesses seem to think that maintaining the quality of the database can be managed by the sales team and the accounting group.  While in absolute terms this might be a bigger problem in smaller businesses without a budget to purchase data hygiene and append services on a regular basis, large organizations could probably save a small fortune in data costs if everyone working with the data took some measure of responsibility for it’s management.

Last week I spoke with a company executive who truly seemed to believe that because the sales team was actively working the prospect database of some 10,000 businesses, they could expect a 90% accuracy rate. How do you tell someone that they’re delusional?

According to Netprospex, the average B2B database decays at a rate of 2% a month, which means that in a year, one quarter of your contact information is useless unless it is regularly maintained. If you believe that  your sales people can adequately manage that job in addition to the real reason you have them on the payroll- which is to sell- then I suggest you sit yourself down with a calculator, look realistically at how many different companies they have contact with in a year and you’ll start to get an idea of how ugly your prospecting base might be if you lift up the lid and look in the box. Not to mention that sales teams are not exactly renowned for their meticulous attention to detail.

Make your data everyone’s concern.  With well distributed and clear standards for how data should be entered, no one who accesses the data base is too big or too small to contribute in small ways, like tagging/flagging duplicates, filling in fields that they might have the information for and correcting simple, obvious errors.

If, like many businesses, your database is key to the success of your marketing and sales programs, everyone benefits when the information is improved.



Avoid a Database Disaster with 5 Simple Steps

There’s no denying that your company’s customer/marketing database(s) is an invaluable asset to your business and at the same time a major pain in the neck.  There are just too many ways that it can be damaged – as far as usability is concerned- and unless you’ve been through it all before, chances are you will not anticipate how you can go wrong.

get help here

It’s difficult to define the exact information you need to input in the first place.  Don’t just go with the software defaults, unless of course it really is important for you to record the President’s secretary’s birthday.

When you’re buying data, it’s equally easy to be seduced by countless fields of nice-to-know stuff, but if it doesn’t stay up to date is pretty worthless in the long run.

When you have different individuals who are inputting data (including the dreaded sales team), consistency can quickly go out the window. While adding partial data seems much better than adding nothing at all, you’ve just kicked the “Duplicate My Records” door wide open and if some of your original source information comes from self-filled on-site forms, you’ll quickly find that much of what people give you is not true.

Complicating the problem of errors in the design of your database and inconsistent input, it’s horribly true that a database is a fabulous example of entropy because the people and companies in your database are constantly changing.

Taken together, these (and many other factors) spell Data Disaster, unless you can consistently follow 5 Simple Rules:

  1. Remove your duplicates and establish standards of how the data in your fields is entered to avoid adding more duplicates
  2. Use it or Lose it.  Untouched data does not remain accurate, regardless of how good it was when it was originally entered or how much you paid for it.
  3. Look at a manual or automated append service to bring your records up to a usable standard. It’s much easier to avoid entering duplicated when you append simple address information against which you can match the files.
  4. Verify your key information.  One thing I can’t personally buy into is to allow anything automated to update actual contact names given the many different ways that job titles can be interpreted. Even using a verification source like LinkedIn can still allow for the insertion of contacts who have already left a company before you even enter them.  Ironically enough, I’m far for comfortable accepting automatic information for C-Level and Board Member contacts in major corporations than the information for their subordinates.  Any data for middle management should be confirmed by a call to the company.  This is where the volume of your contacts will probably be and the most errors.
  5. Stay on top of your data.  Consistently applying a relatively small amount of time, attention and money to maintenance, will help to keep your database as an asset to your company instead of an albatross.







Nothing About Data Cleansing Is Easy

Too many companies are building their marketing programs based on lousy data.  While consumer databases are easily overwhelmed with the staggering volume of available information, B2B databases are inherently more complex and once they start to deteriorate- downright ugly.

This is actually a post for smaller businesses about setting up your database to run an append, but the more you look into the subject, the more you’ll tighten up the controls on what goes into your database in the first place so that you’re not overwhelmed with what are actually the first simple steps. You might even want to consider setting aside a small portion of the budget you assign to any marketing program that uses your database in order to improve your database information every time you use it.

Appending your database is simply a process by which the companies in your database are matched up with those in another master database and once matched, some of the empty fields in your data can be filled with the information from the other base. There are of course limitations to what can be filled in with any hope of accuracy and while you can use appends to pull up standard industry information, phone numbers, some web data and executive names, I’m highly dubious of the quality of the contact, title and individual direct line and email information for anyone but the most public figures within an organization. Additionally, you have to consider the limitation contained in  the phrase “matched with another master database”, because  the match rates might actually be very poor, which means you’ll still have a lot of holes when you’re finished.  Oh yes, and its far from free.

What that means is that before you can move ahead there are three things that must be done:

Select Your Files.  You need to determine which data in your base is worth spending the money on.  Lead data that is very fresh is one thing, but do you really think its a good use of your money to fill in empty data fields for a lead you generated five years ago and never responded to your subsequent efforts to convert?   Once you’ve made that decision, your first task will be to isolate that data. How will you do that?  If it’s by sorting to a code/date/source that was never entered in the first place, you will have just hit the first of what will probably be many snags.

Identify and Remove Your Duplicates.  As with the previous task, this sounds easy but it can be a terrible job, but really, you don’t have much of a choice if you ever want to clean up your data. There are a few obvious places to start. For example if you actually have contacts in your database that are flagged as as duplicates or no longer working with the company and/or you have companies that are flagged as duplicates or out of business, why are they still there.  It might seem as if they are already discounted enough to ignore, but that’s just because you’re not the sales rep who is manually working with the data and might just not notice that little field in the corner that identifies the contact file you just entered your notes and next steps into is the duplicate file?  Sound stupid?  I can assure you it happens a lot and now you have good information in a bad file.  The other challenge many companies will face with the simple question of duplicates is to identify which is actually the good record and which is the dupe that can be removed.  It’s not at all out the question that at some point you’re going to have to put a real set of eyeballs on your data to make the decisions you can’t trust the software to make. Tedious, expensive and time consuming work it is, too.

Clean and Standardize Your Remaining Records.  When you begin the append, mop to clean datayou’ll be able to get a half decent match rate if you’re working with data that has been cleansed.  That means that at the very least, numbers have to be formatted consistently, address formatting and abbreviations also need to be standardized.  There is software that will help you clean up your data and get it into the right format to maximize your match rates.

Right about this point, if not already, you’ve probably at least made a few scratch notes on new database entry policies around data formatting, duplicate checking and key information fields, so that you might not have to go through this again, or at least, not for a while.

The Big Data Issue is BAD DATA

Will the fascination marketers have with buzz words never end? (Well, no actually it won’t)  and now it seems that the talk of the town is Big Data.

For the minuscule percentage of marketers with pristine data and the wherewithal to afford the talent and tools to create added value for their organizations through the manipulation of enormous data-sets- big data is a genuine issue. And, when something becomes a genuine issue for the marquis marketers, everybody hears about it. Leading edge issues are the subject of white papers, conferences and blue ribbon reports, not to mention the marketing of the software to deal with those issues, but they are not what everyday small or medium sized companies should be looking at right now.

Right now, the big data problem is bad data, it’s unbiquitous and tedious little cousin. But make no mistake, bad data is hurting you.

Bad data is limiting your lead generation programs

  • You’re wasting time and money to market to contact who are not there
  • Your response metrics are useless when you can’t tell the difference between not interested and not there- so how will you every improve?
  • Improved targeting and audience segmentation programs are impossible to build with garbage data

Bad data is killing your sales team

  • You’re wasting money on contact attempts to companies and contacts who are not there
  • Your sales team are wasting their time and your money trying to make contact with contacts who will not be involved in a buying process
  • You’re getting far fewer leads to your sales team than you could be

Bad Data is hurting your customer relationships

  • You’re sending communications to contacts who are no longer there. not only does it just look bad, you’re missing out on up-sell, resell and renewal opportunities.
  • Your A/R is stalled when the contact info is out of date
  • Your apparent lack of interest in your customers is creating a hole your competitors will drive a truck through one day

Why is this happening?

Most companies are struggling with data problems because they are holding too many inactive records in their active databases.  A report from SiriusDecisions identifies that every 12-18 months the volume of customer and prospect data is doubling.  List building is like lead generation- first everyone wants more and bigger, until they realize that small and accurate is the only way to go.

If you’re like a third of businesses, you’re struggling with bad data, but not doing anything about it. Roughly another third is relying on their sales teams to update the databases, which is probably worse than admitting to doing anything at all. Sales reps were not hired and have not been trained for their superb attention to detail, patience and perfectionism. You think you’re staying up to date, but in reality your data is degrading and you’re in denial.  Besides, with 3 sales people and 20,000 contacts in your database, how can you possibly think that “sales updating my database” is going to have any impact?

Here’s what you need to do: Use it or Lose it

Bite the bullet now and concede that your database needs some help- or maybe a lot of help.  Consider refreshing your database using an append service to clean up some of the empty fields in your records- although it won’t do much to help you with a lot of your contact information that looks ok but is actually wrong.

You need to use the data. Your first priority is to identify and isolate the good stuff. Email campaigns are where most companies will start because they’re fast and cheap. So start there and flag both your confirmed deliveries and your hard bounces. Start to migrate your data to a mirrored base, only moving what you know is good and when you’re qualifying data bases on a parameter like confirmed email delivery- take the opportunity to immediately ensure you’re moving a completed record with name, phone, address, company, title- the information you need.  If, like many companies your marketing and sales teams are sharing the same database, allow your sales people to flag records that they personally confirm to be good.

Take the data that you know is bad and either start a program to update it and reintegrate into your new active base or lose it.  Hold your unconfirmed data in its own isolated base, ready to update and migrate or trash when you know more about it. It will take time, effort and some money to work through your base, so put data hygeine steps into your sales and marketing processes so you don’t just end up in the same place 2 years from now.

Good data, not more data is your only qualification.

Declining Response Rates – Stop Shooting the Messenger

The most visible and important measure of success delivered to any company by any B2B marketing campaign is the direct response.  It blows awareness out of the water.  A direct response is more valuable than any measure of brand preference or image because it opens a dialogue for more marketing, it opens a door to sales revenue (heck- it might even be a sale) and it’s the only sure way to ever directly evaluate ROI.  You put out a message and a selection of your contacts put up their hands and ask for more.   Marketers love responses and responders…..almost as much as their colleagues in sales. And that’s why the media that can deliver the most direct responses is always the “darling du jour” of B2B marketers.

The challenge that is vexing so many of us now is that real responses are hard to come by…and getting harder. It seems that many people feel this is happening  because the tools we use to drive responses – direct mail, email, voicemail, telemarketing – are losing their effectiveness.  And so, the rush to social media marketing is fueled by the hope that it will somehow fill the void and drive a host of new responders into our waiting (hungry) arms (jaws).

Good luck with that plan.

If you’re serious about improving response rates, the first step is to accept responsibility for your messages and stop blaming the messengers, even though its true that when, for example – email, voicemail, direct mail were the shiny new toys on the block, generating responses was like shooting fish in a barrel.

In the early days, your messages were automatically novel, unexpected and an original approach. The response rates were terrific. But as messages like yours proliferated and dulled those shiny new communications channels, they all moved down the continuum from unique and special, to fairly common but frequently useful, to more of the same old junk.

But, the solution will not necessarily be found with a new messenger. I think what we need to do is take a good look at our messages and figure out why no one can be bothered to answer them.  So, because we all love lists, here are my

Top Seven Reasons Why I Didn’t Get Enough Responses….In No Particular Order

  1. The message was never received.  (Bad data)  If you fail to invest in your data,  you will throw money away on every campaign you execute in every medium with messages that can’t be delivered to people with missing, incomplete or incorrect contact information.  In some ways, this is the worst possible mistake because you’re making the same mistake over and over.  It messes up all your metrics. An undelivered message is like a golf putt that doesn’t make it to the hole. Each has a 100% chance of failure.
  2. The message was unclear. (Bad writing)In order to grab a persons attention you must be direct and crystal clear.  Messages that are filled with jargon, that use a senders “company speak”, that ramble and are simply jumbled and poorly organized don’t drive a response.
  3. The message was not compelling.  (Weak Offer) Was there anything that said “read and act, now?” Don’t list a bunch of features that your engineers think are cool, highlight a benefit that your reader needs (preferably desperately) and if can’t communicate a sense of urgency, why will someone interupt an already busy day and respond?
  4. The message was not relevant. (Bad Targeting)  You sent your message to the wrong person. Either you were completely off base and your product/service and offer were of no interest to the individual or company you sent it to, or you matched the wrong benefit to the title.  As a rule of thumb, you’ll get better responses offering Executives benefits that are relevant to their responsibilities, so why are so many campaigns structured with a single benefit statement offered to all job titles in a company?
  5. The message didn’t speak to current priorities. (Wrong time)  Unless your campaigns are themselves in response to specific triggers, timing can be a matter of luck.  There is only one solution when everything else looks right and that is to keep on trying.
  6. Your message was lost or forgotten before action was taken. (No follow up) You can’t rely on a one time message to communicate any campaign because while rare, it is possible that you’ll strike the right chord, with the right person and they’ll be interrupted before they can take action.  Events can quickly overtake even the most interested potential response, even one that could easily turn into a sale.  So, it’s imperative to make more than one attempt to get an action executed.
  7. The campaign parameters never defined “enough”. (Weak objectives) It’s entirely possible that if you don’t run through the numbers and work with a realistic expectation of what you’re responses should be, you can spend your money without a hope of driving a positive ROI.  For example, I can’t think of a universe where a list of 1000 CEO’s will deliver 100 attendees to anything but the most exceptional business event.

To deal with your declining response rates is a challenge that will require your skill, your hard work, your resourcefulness and a careful but adequate allocation of your budget.  I admit that this doesn’t sound all that encouraging, because it isn’t easy.  But unlike pinning your hopes on the next marketing discovery, if you focus on a brilliant message and stop expecting the messenger to do the work for you, (like in the good old days) you will have a shot at improvement.

The Number One EASY Database Fix

We’re in the middle of a study of customer databases.  It’s actually quite a simple review, but that’s only because our work delivering guided voicemail messages enables a complete analysis of every list we work with.   To run our study we selected a random cross section of campaigns that ran through the first half of 2012.  The full sample came to just over 50,000 records and of course all the programs were business to business campaigns.  For any clients reading this post, let me assure you that your confidence was never breached. We only worked with our internal results spreadsheets.

We also screened out all but customer databases. We wanted to answer the question,” On average, what does the average customer database look like? ” We hope that some answers to that question will help us identify for our clients,the most common areas where their data is weak and how they can get the best return on their investment when it comes to fixing data.

One result has come screaming to the forefront of our conclusions and of all the data fixes that any client might need to do, this one is the simplest and I believe the cheapest to fix.


In  2004 when we ran our first data study, less than 1% of the contact records were duplicates. By June 2009, that number had exploded to 4.55% and it has pretty much stayed there, measuring 4.59% of all the files.

There is a lot of additional information that we’re finding about data and we’ll follow up in future posts, but for now let me suggest that a concerted effort to dedupe your databases could return some big savings in future marketing campaigns built on that data.  Almost 12% of the failed records did so because they were duplicated.  This is an easy, low cost fix.