Today, 67 percent of businesses rely on CRM data to segment and target customers and 64.8 percent of sales reps’ time is spent on non-revenue generated activities. Therefore, B2B brands must prioritize clean data in order to streamline sales revenue and lead generation efforts.

Since the start of the Information Age, people have thought access to information would solve many of the world’s problems. In nearly every case, this optimism eventually gives way to confusion when the access to information doesn’t solve the problems people thought it would.  More information is good, but it also contains more bad information, and a small amount of bad information can drown out the good.  

In sales and marketing, misinformation is usually self-inflicted in the form of inaccurate data.  Companies have always worked with inaccurate data, but the problems created by it were always limited because of the manual nature of the sales and marketing funnels.  With the rise of marketing technology and automation combined with a strong push to automate and scale more personal interactions, the negative effects of bad data are being amplified.  

Before, you might get someone’s name wrong on a form fill.  Now you’re more likely to get their gender wrong, identify them as in the wrong industry, think they’ve been downloading your content and misidentify their political party affiliation.  So, you end up sending a unicorn themed mail piece to the wrong person, talking about the benefits of your CRM plugin designed for sandwich shops.  This person used to own a sandwich shop and is now in sales in the power washing industry.  They haven’t seen any of your company’s emails, but their security did check your marketing email links for potential viruses before sending marketing messages to the spam filter. This highlights how important up-to-date and accurate information is. The more information we have, the more opportunities there are for inaccurate information.   

Most of these examples are high level inaccuracies that show themselves when you do more segmented campaigns. Data inaccuracies can cause campaigns to be ineffective when the whole purpose was to utilize detailed data to deliver more relevant campaign content.  Also, inaccuracies with phone numbers, addresses, emails and contacts that are no longer at the given company cause even more waste in sales and marketing.  

There are many data providers now with massive volumes of company, contact and demographic data for both business and consumer marketing.  Even the best of these companies constantly struggle to keep their data clean.  A company’s sourcing and cleaning practices must be considered when looking for data. However, many of the best-known companies have fatally flawed practices. In some cases, they benefit directly from the misinformation.  

B2B companies think of LinkedIn as a premium source for business contact information.  But LinkedIn data is crowdsourced and with nothing to maintain the accuracy, we estimate up to one-third of U.S. profiles on LinkedIn are fake or abandoned.  It recently came out that hundreds of thousands of Google Maps listings are fake. This inaccurate data ends up making its way into companies CRMs wreaking havoc on the sales and marketing funnel.  

I’ve singled out LinkedIn and Google Maps because they are so well known.  All databases that allow the public to create or alter their data have issues with inaccuracy, especially when they have incentives for misinformation.   Take the case of Jigsaw, which was purchased by CRM behemoth Salesforce in 2010 for approximately $142 million in cash, plus bonus’, and rebranded as Data.com.  Jigsaw used a crowd sourced data model allowing users to upload their sales and marketing data for credit they could use to download new records.  

As a result, Jigsaw quickly expanded the size of their business data. Yet, they did not have a strong mechanism to validate and clean their data, and they ran into quality issues.  Users were also uploading inaccurate data to start with, as well as editing existing records with inaccurate information.  It’s rumored that Salesforce is throwing out Data.com and working with D&B because the Jigsaw dataset became notoriously bad. 

Maintaining information accuracy is a difficult and never-ending task that has overwhelmed even the largest companies.  With easier access to large amounts of information, data companies have found that owning data is easy, but identifying the accurate versus inaccurate data in a large data pool is increasingly difficult. Even large companies are poorly equipped to tackle the issues that arise when managing large amounts of sales and marketing data. Additionally, sales and marketing departments complain about data accuracy, but they have no expertise with data and are not willing to get their hands dirty with it. They are right, that isn’t the job they signed up for.  Even data companies are typically better at selling data than they are at maintaining it. B2B companies do not need to have in- house expertise in data, but in order to sustain sales revenue they do need to make data accuracy a priority. 

In fact, MountainTop Data’s internal studies have shown 50 percent of a B2B marketing database goes bad every two years. The largest cause of this is people changing jobs, but it also includes company mergers, domain changes, promotions, new hires, company and contact relocation, and email and phone changes. 

Maintaining accurate CRM data for sales and marketing can also be looked at with the 1-10-100 rule.  This rule says it costs 10 times as much to clean data after you purchase it and 100 times as much to do nothing.  So, what is the cost of dirty data? Consider at least 50 percent of your sales and marketing budget wasted.

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Dirty data includes both records for contacts that are no longer with the company, companies that are no longer in business, and inaccurate information in critical targeting or contact fields.  An inaccurate email is bad but having the wrong industry or company size assigned to a company can have the same impact, and it can spread across all records in that company.   

Additionally, one of the most obvious effects of dirty data is improper expectations. Thinking you have a large, accurate list of target accounts when you don’t can cause you to improperly set expectations for your sales and marketing teams, which would end in teams focusing on the wrong problem when they ultimately don’t generate expected results.  

In fact, poor CRM prospect data is responsible for a loss of 27 percent of each rep’s total selling time.  When you have inaccuracies in your target fields (industry, company size, geography, etc), you will end up sending campaigns to the wrong audience.  Poor quality CRM data also hurts the morale of sales and marketing employees that are working with it.  It’s disheartening to pour your heart and soul into a campaign just to find out your efforts were undermined because you started with bad data.  Or for a sales development representative to make 200 calls a day and have bad phone numbers and inaccurate personal data.  This type of data issue regularly leads to sales reps saying they don’t want certain leads anymore because the data is too inaccurate.  Overall, pursuing the wrong accounts or having inaccurate contact information is a waste of time and resources for everyone.   

Also, there are additional costs for dirty data when you look at the CRM, ERP, and marketing automation systems used today.  Most of these systems have a cost for the volume of data you keep in the system.  Companies that use multiple systems are paying multiple times to house dirty data. If you look at the cost of systems like Salesforce, Marketo, Pardot, etc., compared to what the data costs that you put into these systems, it’s easy to see how the cost to house bad data can quickly become a significant portion of your data budget. 

Dirty data within emails can get marketers kicked off email delivery platforms and can lead them to getting blacklisted.  A lesser known but just as problematic of an issue is inaccurate targeting of email campaigns due to information like industry and geography being wrong.  Complaints from recipients can also have marketers booted from their internet service provider or email delivery service.  

Improper targeting in email campaigns can also hurt your SEO. By targeting the correct audience, with accurate data, you increase the number of purposeful searches for your site and users will tend to spend more time on your site, decreasing the likelihood for them to go back to Google and search for the same keywords.  When you target the wrong contacts with your emails, it has the opposite effect. This is important because Google SEO thinks your site doesn’t fit the keywords searched if visitors quickly leave and run the same or a similar search again.  This causes them to lower your search ranking for those keywords.   

The easiest way to keep your data clean is to start with clean data.  The two main areas to cover here are thoroughly vetting new data providers and having all contact and account data automatically fed into your systems screened.  The type of screening will depend on the volume of data you get this way.  If it’s manageable, someone can manually review it. Otherwise, filters can be set for what is manually reviewed or it can be outsourced to a third party.  

Yet, reviewing data providers is usually easy, so it’s advisable to request and review a contact data sample of a reasonable size before making any purchase.  The number of records in a sample is crucial because if they only give you five records, they can screen them, then only when a list is purchased is when you can see what they’re really providing.  Reviewing the sample will show you the accuracy of both the individual contact fields as well as the overall targeting. 

Contact data goes bad quickly and if you start with accurate data, you will still need to regularly clean your contacts.  Flagging and removing email bounces is easy enough to do, but many emails will never bounce even when the contact is long gone.  The best solution for a thorough cleaning is always a third party that can leverage a large internal database and go deeper than email verification.

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According to the 2019 State of the Cloud Report from Flexera, companies plan to spend 24 percent more on public cloud in 2019 in comparison to last year. The extra spend results in 24 percent more data migration because data has to get to the cloud somehow.  Additionally, enterprises spend even higher, with 38 percent exceeding $2.4 million per year and half (50 percent) above $1.2 million per year.  When data migration is executed poorly or fails completely, the money spent on migration is lost.  And that’s not the only fiscal impact of a data migration gone wrong. 

Simple missteps when moving data from one system to another can have a negative ripple effect throughout your marketing process and carry over into sales, potentially sinking your sales and marketing efforts for months depending on the severity of the failed data migration.  

I’ve been involved in hundreds of data migrations, both for internal marketing data and overseeing MountainTop Data’s client data migrations. We’ve had to pick up the pieces of a client’s data after they went through a poorly conceived data migration and saw small oversights wreak havoc on our own marketing campaigns. Today, it is estimated that 87 percent of online marketers use email as it is still considered the number one source for online sales and is used more than any other form of lead generation. Hence why it is paramount that data migrations need to run smoothly and efficiently before it stalls marketing efforts.  

Therefore, accurate company and contact data is critical, and a company’s internal information on clients and prospects are frequently overlooked when making hardware and software upgrades.  Assuming new systems will properly identify, process, and accept your data is a big mistake.  Every situation varies and close attention should be paid to all data fields.

Data migration typically includes three steps: extract, transform, and load. Before extracting from your current system, create a backup.  Without a backup, all data could be lost if something does go wrong. 

Extract

Some systems have integrations that allow you to define data paths and migrate directly from one database to another. A common step is to export your data from your current system into an excel spreadsheet or another common database file. The structure of related fields in your current database may require you export several data tables, so be sure to export all fields including unique identifier keys (contact ID, company ID, etc.), so records can be easily tracked.

Transform

This is the most important step in a data migration because you must look at each data column. Check that all data has exported properly and inspect the data formatting for each. Specifically, ensure that all records and fields from your original migration are included as file handling special characters are different from your initial database. 

It would also be wise to proceed with caution as some file types will see a prompt to separate the data into multiple fields, causing a data offset issue. Thus, check each field to assure it’s not formatted in a way that has caused data loss. This can be as simple as losing the 0 from the front of zip codes to an error identifying the data causing a null value. Lastly, check that fields with a lot of text haven’t been truncated by a restriction on the number of characters allowed for that field in the formatting. 

Load

Once your file is clean, you’re ready to import the data into your new system.  Depending on the data structure in your new system you may need to separate your file into several imports.  Before you import, reformat fields in your file to match specific format requirements for the new data location. You would have learned these on your test run. 

In addition, you need to spot check your new data set to see if there were issues you missed and let anyone you will be working with to raise the alarm if any data abnormalities are noticed.  Finally, keep a copy of the original data set for at least a couple months. This will allow you to revert to the original and redo the migration if necessary.  

The key consideration of migrating data into the cloud is a simple one: data is only useful if it is accurate.  Data improperly migrated into the cloud and into a new CRM could render your sales team’s accounts missing information — or missing altogether.  The purpose is to oversee a smooth migration, encouraging account managers to incorporate a CRM and utilize the technology to achieve lofty sales goals.

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At the same time, social media marketing, across a variety of new and shiny platforms, can seem enticing, after all, everyone wants to be marketing on the “next big thing.” While other marketing channels can appear to be good options, when it comes down to the numbers, email marketing is still the best bang for your marketing buck. The big difference is now you only get rewarded if you know what you’re doing. ROI in email marketing remains high because email is ubiquitous, convenient, extremely low cost and highly scalable.  

Every hot new message delivery system either gets replaced by a newer system or gets used so much that the target audience gets desensitized. Email marketing has diminished in its effectiveness in some respects over the last decade, but it still holds the highest ROI of any marketing channel.¹ Social media has cut into this some, but social media doesn’t have the 1-to-1 relationship that email has; a much higher percentage of emails are viewed than social posts.  It’s estimated that when it comes to marketing, email is nearly 40 times more effective than Facebook and Twitter combined.² People are twice as likely to sign up for a business’s mailing list or newsletter than to interact with a Facebook ad.³  

Email is effective partially because it works on your schedule and doesn’t get offended if you say no or ignore it.  We all have a phone in our pocket, but would you rather get a call from a sales person or an email?  An email sits in your inbox until you’re ready to look at it and it doesn’t demand interaction or a response.  By 2020 half of the worlds’ population will use email,⁴ and the ones who aren’t using email aren’t shunning it by choice. Email is your digital home. Social sites and all other marketing channels have boundaries—be it geographical, topical, or generational—but email is a standard platform used by everyone worldwide.  In fact, a lack of email address is a barrier to entry for nearly every online community in use today.  

Email marketing extends beyond people who sign up for your newsletter. You can expect a higher response rate and overall interaction from your company’s opt-in newsletters, but those contacts are already interacting with your brand. To generate new business and maximize growth you need to be in front of people who aren’t already listening to you. The most effective way to do this is to purchase a list.  While lists purchased from a list vendor will always give lower open and click rates versus your pre-existing opt-in mailing list, they still have the best ROI of any new business generation channel.  There are many issues to consider when marketing to a purchased list, and though it is a very powerful tool, when used improperly it can cause problems. 

The first thing to avoid when purchasing a list is purchasing inaccurate or outdated information. Emails for contacts who haven’t been at the job for years (or even one day) don’t do you any good. Using inaccurate emails is far worse for your campaign than someone simply not receiving your message. Sending to emails that are no longer active will hurt your sender reputation and cause good emails to get filtered out of the inbox and into spam folders.

Email sent to the wrong person with an irrelevant message for their needs can result in complaints that hurt your ability to deliver emails to inboxes even more. It’s important that your message and data is highly targeted to avoid spamming irrelevant companies and contacts. So not only is it important that the email is accurate but also that the other targeting information (industry, title, company size, etc.) is correct. When purchasing a list, make sure you get samples from several vendors first and check them for accuracy.  

A reliable data company will verify its emails every 30 to 90 days. There should be other verifications as well, since email verification alone is an inexact science. Ask any list vendor how often they verify their data and what verification steps are taken. A trustworthy list vendor will be able to answer this type of question.  If they stop at only email verification, you’ll likely find a high percentage of their emails are inaccurate.

Finally, once you have the list purchased and are ready to begin your email marketing campaign, make sure your message is clear, concise, and most importantly, follows the rules and regulations [of your country]. For new business generation, email marketing best practices include:

• Relevant Subject Lines
• Limited use of Images
• Straightforward Messaging
• Simple Call to Action Early in Emails
• Identifying the Messaging as an ad
• Including your Company’s Address in an Option to opt out

Email marketing is consistently cost effective, scalable, and accessible while remaining familiar and easy to use, so it is worth continuing to invest in, both financially, and investing the time to remain well versed on how to acquire a potential audience, and how to effectively and successfully reach that audience. 

The post In the Broad Landscape of Digital Options, Email Marketing Remains King appeared first on SiteProNews.

I’m a huge proponent of lowering barriers of entry so the best ideas can bring the best products and services to people.  But I’ve recently started questioning this when it comes to technology that scales.  When in the world at large a technology gets both advanced and simple enough for non-experts to use, it becomes dangerous and artificial barriers to access are typically established.  You don’t want crisper gene editing kits at your local hobby shop.  I was talking with Scott Brinker, of chiefMartech.com, a huge proponent of MarTech, and he likened MarTech to the Sorcerer’s Apprentice: when an inexperienced person can get access to such powerful tools, things usually go wrong. 

Because marketers are competing for attention, they are in a constant arms race to outdo each other with the newest technology and the best techniques. Effective marketing techniques and channels either get replaced by something more effective, their novelty wears out, or they are so effective that they get overused and people stop paying attention to them (sign spinning, neon lights, and email marketing?).  

Every new channel is most effective when it’s novel, then people get used to it and its effectiveness is diminished (that said, if it isn’t just a gimmick it will continue to be effective, just less so).  MarTech and AI are allowing the hungriest marketers to push the limits of scale and personalization within the most effective marketing channels and techniques.  The slicker we as marketers get in executing these techniques the more likely we are to breed hostility in the very people we are trying to connect with and ruin the effectiveness of these channels.  

Back in the day, email allowed even the smallest company to send very inexpensive messaging to massive amounts of people at very low cost.  Companies with great ideas, but little means to let people know about them, could suddenly get the word out and compete with larger brands.  Many of these companies had great ideas, but no experience or care for best practices.  People with little or no sales and marketing experience suddenly had access to powerful distribution tools.  Low cost also means low consideration, so massive amounts of poorly targeted and poorly conceived emails were sent out over the years.  

Companies that would not have the means to distribute their message or would have taken greater care in what they were sending out, started undermining the trust in an otherwise very effective channel.  This combination of cheap access with little experience and little to lose is what makes startups so dangerous.  They have no brand and no clients, so why not move fast and break things.

Companies frequently choose their brand archetype, rather than growing into one.  They decide who they want to be to best sell within their market, and they fashion themselves around that archetype.  This can be problematic, like the boiler room that has posters on every wall about having great employee morale. You can change who you are, but you can’t select a brand archetype that you are not and be it.  If you aren’t the archetype you are projecting, it will catch up with you.   Your audience will see through it, they will tilt their head when looking at you and say, “He looks like a Hero, but something’s off.”  Then, like a David Lynch film, the façade will start to crack, and everything falls apart.  

There are 12 common brand archetypes; I’d like to add a 13^th.  Pretending to be something you aren’t will cause people to lose trust in you, but the 13^th archetype looks to perfect, personalize, and scale this practice.  Call it the Chameleon, or the T-1000. This brand has no identity, but technology has given it the ability to mimic whatever identity it thinks you want to see.  The Chameleon knows everything about you and has an archetype assigned to every target.  When you come to its website, call in, walk in its doors, open a browser, or answer the phone, you see an archetype designed just for you.  The Chameleon is the unholy offspring of Donald Draper, Big Data, MarTech, and AI, and you’ll never see it coming because it looks like exactly what you want. 

Sounds great for marketing, right?  Every company wants a marketing T-1000, but what if every company has one?  Not only is it an arms race where every brand has access to these powerful tools, but people don’t like being targets and they will adapt.  In this case, people will lose all trust in marketing in general.  Just like they have in the past on individual channels, when you get too good at making people do what you want, their only defense is to lock everything out.  At this point, marketing will enter the dark ages.  People will only listen to people they know and trust, and the reach of marketing will shrink down to direct human interaction.  Startups, as we know them, will be dead. Also, large, established brands will dominate the marketplace and innovation will screech to a halt.  In the end, the customer loses. 

The customer loses because we failed them as marketers. We violated their trust, became greedy and lost sight of our purpose.  There’s plenty of reasons this won’t happen quite like this, but it’s already happening to some degree, so just make sure you don’t fall victim to it.  To protect yourself, be careful not to abuse the trust the public still has in marketing.  Lastly, marketers should build a strong “human” brand through MarTech in order to be authentic and ensure there’s a real live human present.

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