While its great to see so many marketers enthusiastic about their inbound lead generation programs and discuss metrics and success stories on how many leads came through which can be added to the funnel, the process of inbound lead qualification still remains the ignored step-child of marketing and sales. While some companies are not in agreement whose responsibility it is, others don’t have a formal process in place simply because it’s assumed that when sales calls into these leads, they are going to qualify them while they are trying to sell to them anyway right? Wrong! In order to have an effective lead generation machine going, a very clearly defined lead qualification process has to be developed and dedicatedly focussed on only qualifying leads before they are passed on to sales, the lead nurturing cycle or the completely “not qualified” pile. Whoevers responsibility it is, unless inbound leads are qualified as soon as they generated, there will be a lead in the process which can result in missed opportunities or simply result in sales wasting their time going after leads which are not likely to go anywhere.

Here are some simple points to follow to get a solid qualification system in place:

1. Decide whose responsibility it is to qualify leads is it marketing? inside sales?
2. Define an inbound lead qualification program as a seperate responsibility not clubbed with sales
3. Decide what is the maximum time a lead is allowed to sit before it gets called and qualified and enforce this practice. The first few hours after it is generated is agreed on by b2b marketers as ideal and preferably not more than 24-48 hours later.
4. Chalk out and agree on what will be considered a “qualified lead” decide what criteria will define what will be accepted by both sales and marketing as a qualified lead and be sure to address any grey areas. Agree on a scoring system where leads can be qualified into seperate buckets where A can be highly qualified leads which need to be engaged immediately, B can be qualified but needs to be nurtured not engaged right away and C can be unqualified or dismissed leads which have no potential.
5. Work out action items for each type of qualified lead for example type A must be passed on to sales with an alert immediately, type B can be sent back to marketing or added to the lead database to nurture and type C should never make it into the database or CRM.
6. Narrow down on a small set of questions which can be used to qualify leads. The questions should be simple and aim towards determining the criteria we talked about in point 4 above.
7. Measure & share results. Track few but importnat metrics such as the percentage of leads that get qualified, conversion rate and share this information with the inbound marketing team and sales team to help guage what is working and what is not.

If you can get this process in place and keep it consistant regardless of what is happening with those responsible for lead generation and those responsible for prospecting, you’ll have:

• A happier and more efficient sales team
• A more efficient lead generation system
• Less wastage
• Higher conversion rates
• A database free from junk leads which have no potential

It’s that simple.

Data Strategy Magazine published reports of a study carried out in the UK by Kalido where they researched companies with a turnover higher than $500 million and found less than half of the respondents satisfied with their database quality. In the report Data Strategy Magazine published:

Nearly one quarter of respondents (24 per cent) said they were not very or not at all satisfied with the consistency and accuracy of master data in their company and that data issues were many and constant. Just over one third (35 per cent) said they had no data issues at all. The largest group of 41 per cent fell in between, being somewhat satisfied, but with a few data issues still to resolve.

Given that marketing organizations of such large companies need to rely so heavily on their data for driving new revenue, its surprising how little attention is paid to it’s upkeep. Perhaps if their customer and marketing databases were valued monetarily as a company asset and this value was tracked through the year based on how much of the data is active and useful in developing future business, it would get the kind of attention needed. While marketing budgets are generously allocated towards events and campaigns aimed at generating new leads, very few VP’s of Marketing or CMO’s apportion an amount towards maintaining, cleansing and enriching existing data which incurred a sizable cost to build earlier. The article in Data Strategy goes on to say:

As part of the study, companies were asked to put a financial value on the costs savings or increases in revenue that might result from data quality initiatives. The majority (57 per cent) were unable to answer. Among those who could, the average benefit was put at $38 million. 

Thats no small change in potential revenue and it may have been possible by budgeting a fraction of that amount in data cleansing and putting in a more stringent policies to keep data quality in check monthly or at least quarterly. It’s not just the large companies in the UK which suffer from data quality and management issues, we can only wonder what the results would show if the same survey was carried out on the Fortune 500 companies. The company database is a valuable asset, treat it like one!

Have you ever moved house where everything you had needs to be moved and looked at it as an opportunity to get rid of what you wont be needing or replace what doesnt work anymore? It’s an almost natural chain of thought when you are moving things to a new setting that you would like to bring with you only what you need and leave behind what you dont need. The next time you need to migrate your CRM data to a new system or are in the process of overhauling your CRM, then look at it the same way. As an opportunity to cleanse your CRM data rather than as just a painful migration process which is a necessary evil to shift to a better system. 

Even the best CRM, lead nurturing or marketing automation software won’t deliver magical improvements without ensuring its fed with quality data and if you are going into a migration with data that hasn’t been monitored for quality for a longer spell, then it’s not likely the new solution will function at 100%. Migrating your data can be a fresh start of sorts and give you the chance to overhaul your data completely once and then put in a periodic and frequent review process to keep the data at peak performance levels thereafter. Here are a few things you can do before the data is moved to its new location:

• remove junk records 
• remove any duplication of records, accounts or contacts
• verify and update email addresses
• validate and update postal addresses, urls, phone numbers etc
• check for and filter out contacts and accounts which are no longer active
• append any missing data points for imcomplete records
• add any additional fields or data points which could be valuable like SIC codes, alternate currencies etc
• normalize and format data
• make any changes to the format or structure of the database

Once the big task of cleansing the entire database is completed, the task of maintaining that level of quality across the new system becomes incremental and won’t be as difficult. If you are planning a migration, plan a clean up too.  It’s a good time. It’s an opportunity.

For more on data cleansing best practices download a free copy of 7 Tips To Healthy CRM Data – CRM Data Management, Cleansing & Enrichment Best Practices

The interesting thing about the economy slow down and its impact on marketing as well as sales is that it’s driven us all to do more with less. Yes budgets are tightening, recruiting is reducing and the workforces are either downsizing or remaining constant. Sales and marketing quotas? No, they haven’t reduced. They have gone up. However it’s not just the recession and low budgets which are making businesses think of alternatives to increasing workforces to do more. It’s part of the evolution of businesses in general and how staying lean and being able to contract certain activities to dedicated providers started becoming a logical strategy. The noose around budgets in this recession is just going to push this trend further as businesses seek alternatives to scaling their interal workforces and operational costs while scaling their business.

How The Virtual Workforce Is Changing Everything by Jack M. Germain is a great read on how perceptions on workforces are changing. Marketing data management is an area this applies well. Building, maintaing and managing lead and marketing data is a time consuming and tedious process but it needs to be done and needs to be done very well. Working with virtual teams at other locations or professional solutions providers in this area is a good alternative for marketers to explore at this stage especially if they are considering hiring more staff to manage marketing data. There are several companies with expertise in list building, lead qualification, lead profiling, CRM data cleansing, email list management, data append and enrichment and more. Other than the more obvious benfits of cost and flexibility paying for support as and when you need it, it can really help free up your internal teams time to focus on other areas such as inbound marketing, lead nurturing programs, social media marketing and generating newer sales ready leads instead of spending it on data.

Perhaps you’ll run some risk of engaging vendors or providers who don’t gel with your requirements till you find one that works for you and build a relationship but this is a risk you face while recruiting a new person for the job too. While considering how to re align your existing marketing team to meet lead quotas give some thought to using vendors for your marketing data needs. It may just give you the edge you need. 

Have you ever thought that your last b2b marketing campaign was not really as ineffective as it may have seemed? Are you sure your CRM or lead management software analytics tools are not blinding you with wrong reports? 

Alright. I’ll admit it’t completely wrong to blame CRMs, lead nurturing software, lead management tools or even email marketing applications for giving anyone wrong reports or false analytics of the effectiveness of your campaigns. Analytics and reporting are based on logic and calculations, they can’t really go wrong. If there can be anything to take the blame for erroneous reports, its the data!

Imagine you spend several days brainstorming and trying to come up with a copy for an email campaign that is so compelling and so well crafted, that it should be enough to lure readers to your sign-ups or landing pages and generate a flow of leads for you. Imagine you select 1000 prospects from your marketing database and send your “sure-shot” email to them as you wait in anticipation for the results. Imagine you watch your campaign performance results and learn that only 100 of your thousand leads actually opened your email and 5 of them responded showing interest. That’s a 10% open rate and a 0.5% sucess rate. Does that mean your email campaign was a failiure and you need to start from scratch with a new copy?

Analytics and campaign reports are only as accurate as your data. They will give you figures on the effectiveness of your campaign assuming every one of your leads and contacts was a valid, active prospect and your contact data 100% accurate. If that campaign was sent to 1000 contacts of which 500 were not really the right people to target, 100 of them were no longer with the same company as when they were added to the database and 100 email addresses were wrong or changed, you effectively ran that campaign on 100 prospects. Your open rate would have been 33.33 % and your success rate 1.67%. So when you send out an email campaign and analyze the results, ask yourself:

• Is every contact on the list a valid decision maker and receipent for this message?
• Is every contact on the list still with the target account? Have any of them left the company?
• Is every email address valid and active? Are there any on the list which are destined to bounce before an email even goes out to them?

It’s back to the office and back to work for most of us after the holidays. Its time to kick off the new year with some serious selling and everyone is charged up to drive more revenues this year. If you have been making resolutions for 2009 and any of them involve better practices to generate more leads and generate more revenues, then here is one which will really yield results:

Keep your B2B marketing and lead data as clean as a whistle

We have done a number of posts over the last year on b2b lead data cleansing, how to go about it and how valuable it is to have regularly cleansed and updated data. If you need re-affirmation just how valuable it can be then you really have to read Ardath Albee’s recent post “Lift Revenues 70% By Cleaning Up Dirty B2B Data”

The finds of the SiriusDecisions study that organizations can realize 70% more revenue from data quality just resonates how important data quality is to better results and increased revenues. Like any new years resolutions it’s easy to resolve that you will ensure high data quality standards in your CRM or marketing data but the success lies in carrying it out with a dedicated and constant effort all year round. It has to be an all round initiative to check data quality and integrity at each and every source, cleanse existing data, weed out dead contact data, add newer records and append data points to add value to existing ones. 

Investing time and money in clean and higher quality data is the resolution that every marketer should think about making this year. Why? Isn’t the chanace to increase revenue by upto 70% a good enough incentive?

Every marketer should be proud of his/her database. It’s not till you actully run into a situation where you wished you needed something more from your data that you actually realize that thiings would have been more efficient “if my data had this” or “if only my data didnt have that”. It’s a good practice to run through your marketing database from time to time and ask yourself if you are happy with what is in it or is there something that needs to be done.

We didn’t really want to do a “Cosmo” style self test but here is a very quick check with few of these questions you can ask yourself to know if you are happy with your marketing database and how we at ReadyContacts can help you with anything you need to make you happier with it. Check it out!

So are you happy with it? How did you fare?

Having checked out Mike Damphousse’s blog post Ethics & Wonder/Amazon’s Mechanical Turk/Kiva on his experience getting a data related task done through the new online marketplace, I had a chance to check it out myself and ponder what this means for us as a B2B Marketing Database Management company. Amazon’s Mechanical Turk has been making buzz waves among marketers among other professionals who have been exploring to see just how they can leverage this to get some of the more routine tasks done. Also getting them done at a very competitive cost by putting them on the listing for providers to bid.

Essentially an Odesk or Elance of task related work, Mechanical Turk is a market place for both providers and requesters of very process oriented tasks like researching, identifying, labeling, transcribing and data related tasks which need some amount of human intelligence as opposed to tasks that can be automated. With several willing providers who can work from the comfort of their homes a lot of these jobs can get done for a fiercely competitve price which even outsourcing companies wouldnt be able to match given their operating costs. Will this mean all marketing data related work is going to head towards this?

I’m not sure it will. A good part of what we do at ReadyContacts does involve that “human touch” simply because there is a difference in quality between automating that process and using human intelligence to get the results. For example we could simply build B2B decision maker lists by pulling records from an internal database and delivering them at a competitive price but we don’t. Our team calls into every target account and locates decision makers by asking others in the company for their specific job role rather than their job titles. Eventually a sales person will need to go through this step to identify if they are really talking to the right decision maker. Calling in to build a list is a lot more expensive but in the bigger picture, we deliver something that will save our customers time and help them get to their decision makers quicker. 

Similarly there are de-duplication applications available that will help you clean your CRM data and remove redundancy and help you lower costs as against hiring someone to do this. Will it work the same? Not entirely. For example, it would help remove two accounts titled “Citi Group” or two leads named “John Smith” but it wont know “Peoplesoft” is a part of “Oracle” or know if a certain company has been taken over, merged or a lead is no longer working in the same company. The same goes for email verification and appending. There is some human intelligence required in most of these tasks to do them better. Does this mean there wont be room for ReadyContacts and other B2B data companies?

Well Odesk and Elance have been doing millions of dollars worth of software development projects for the masses with very capable developers as far as India, Israel, Ukraine and Singapore sucessfully delivering projects. So I’m sure this can be replicated with Mechanical Turk for other tasks. However Odesk and Elance haven’t put larger software companies like Infosys out of work, its only opened a door to the masses as an affordable option to getting development support and Mechanical Turk should have the same effect. We’ll have to wait and watch.

Any readers with experiences having used Mechanical Turk for any of their projects?

Your CRM data is probably one of your organizations most valuable assets. Companies can go through great lengths to protect and secure their CRM data but just how much emphasis goes into the quality of the CRM data? Everyone is well aware about the value of their organization’s CRM data and if there was a straightforward way to put a financial price tag on them perhaps it would put things into perspective better. However CRM data is a perishable asset and left on its own it doesn’t appreciate like an antique with time, it’s value will diminish unless you look after it well. Although data quality management may rank among the most neglected area of CRM management and definitely one of the major pain areas for administrators and managers, following a strict CRM data cleansing and data enrichment regiment is what will help maintain and enhance the value of your data.  

Here are some practices to keep your CRM data quality at its best:

Identify A Drop In Data Quality Quickly

Bad data is often ignored until it really starts to affect daily work by which time it needs a lot of work to get it back in shape. Its important to identify whose responsibility it is to monitor the data quality and keep the maintainence process going on an ongoing basis. Whether its a weekly scan of records to see if outwardly everything looks alright or a periodic email or contact sample check, keeping an eye on your data will help you identify changes in quality earlier rather than later. Sometimes your sales persons or marketing department who frequently use the data to call or email prospects or customers using the data will be the first ones to experience any change in quality and keeping a regular and close feedback loop will help you know how up-to-date your data is or what issues they face while using it.  

Have An Organizational Policy On Data Standards

Bad data in. Bad data out. While CRM administrators and managers are finicky abut ensuring  any data they upload into their CRM is checked and entered exactly how it should be, most CRMs are accessed by several end users across the organization and there is very little control over what data is entered or edited and how it is entered or updated. This is where it can start going wrong. Educating the end users or the company’s data standards and making them aware of healthy data updating practices can help standardize what goes into the CRM. For example if one user enters contact names in the form of initials with currency values in dollars and another enters them as full names with currency values in increments of a thousand dollars there is bound to be a data which is not standardized. Coming up with a well defined data standards policy which is made available to all end users can help considerably.

Put In Stringent Quality Checks At Your Data Sources

CRM data usually comes from several sources from conference lists, whitepaper downloads, website form fills, purchased business contact lists, online ad clicks, business contacts databases and more. Common practice is to upload them to the CRM straight away assuming it can be normalized or filtered later. Its a good practice to manage, normalize, format, qualify and filter out your leads outside your CRM and then have it uploaded so that what is not valuable or quality data does not get added. We’ve covered more on this in an earlier post titled ‘Data Management – Manage Your Leads Outside Your CRM‘. If you check and clean your data right from the source, it will save you a lot of trouble later. 

Check For & Tackle Incomplete Records

Despite most CRMs having validations to check for mandatory data fields its not always easy to ensure a value for every field at the time when a record is generated. For example if your contact source is a conference list of attendees with only contact names, job titles and phone numbers, although it’s been added to your CRM, it has very little value if it needs to be used in an email campaign or a direct mail reach out. Appending missing data is not always easy to automate and often does involve a lot of manual effort which will seem time consuming. However it is a necessary evil and a periodic data append effort for missing data is important.

Check For Duplication And Redundant Data

Duplication of records and having large amounts of junk data is a sign of a sick CRM database. While putting in software checks for validating records and ensuring an entry is unique is a preventive measure thats good to have in place, there are a number of software or technology based deduplication services which can help weed out duplicates some of which are mentioned here in a previous post. With a growing number of leads coming through sources like form fills and online sources where leads can often fill up gibberish values, doing regular scans for such junk records will help you keep your data free of what should not be in there. Its importnat to note that having a lot of duplicates and other redundant data can result in your analytics and reports reflecting false results so it has to be kept in check.

Periodically Filter Out Expired data

Companies and organizations merge, get acquired or shut down, contacts change addresses, change jobs, move within an organization …CRM data does expire. This is an area which is not easily automated and again does require a considerable investment of time and energy. The more regularly you can carry out a check for expired data, the healthier your CRM will be. A database which remains untouched or unchecked for an entire year can see as much as 30% expired data and the longer you have between checks, the worse it can get so making sure its checked periodically is paramount. While being able to run through the entire data once every quarter is ideal, twice a year should be the minimum.

Enrich Your Data, Increase Its Value

If data cleansing is what helps you maintain your database quality then data enrichment is what will help you enhance your data quality and make it more valuable to the end users. Ask yourself what additional data points in each record could help your users do more with the data and give them a better insight on each account. Would it help to have the annual revenues listed in multiple currencies? Would it help to have a list of all countries each account operates in? Would it help to have a link to the press releases of each account to stay updated on recent events? These additional data points can be added with a data enrichment effort after identifying what additional data would help provide value.

If you practice good data management practices and implement a constant cleansing and enrichment process for your CRM you will be able to actually realize its full potential. Thats when your CRM data is really an asset!

If the need to squeeze everything possible from tight marketing budgets wasn’t already enough, the current enconomic meltdown is just going to make marketers even more accountable for every dollar spent and squeeze even more results from every campaign. Direct mail campaigns wont be an exception and being more expensive in terms of designing the copy, printing the material and postage costs involved, the quality of the direct mailing list is where the focus will have to be. 

A mailing list scrub and data cleansing effort is on several best practices guide for improving results on direct mail marketing campaigns. Rightly so since the worst possible scenario for a well drafted and carefully thought out expensive direct mailer is not getting to its intended receipient. The number one cause? Wrong or incomplete contact address data. So why should you use a list scrub before launching your campaigns?

1. The cost per lead of direct mail marketing is amongst the highest and can average between 1$ to 10$ so every mail that is not delivered to its target adds up to a significant wastage.
2. Non Standardized addresses make it difficult to interpret correct locations and often result in delays. The small task to standardizing addresses and normalizing formats can go a long way in saving time and money
3. Missing zip codes, state codes or street names are common in a lot of databases and often overlooked while labels and envelopes are being printed. Small omissions. Big cost.
4. Addresses do change from time to time and data does go bad. Verification will help filter out redundant addresses from your database and update them.
5. The incremental cost of cleansing a list may add cost per lead but will in fact save a lot more by increasing accuracy and delivery.