Modern Sales & Marketing

How to approach Twitter & LinkedIn engagement strategy for better social selling

Twitter and LinkedIn both offer many opportunities for engagement with potential customers, influencers and partners. It is important to consider both how and when to engage with prospects on these platforms as well as exactly what happens when you engage.

Engagements types on Twitter & LinkedIn

The power of Twitter is that it is a completely public network. You can engage with just about any other account on the platform in various ways. You can like or Retweet Tweets, follow accounts, mention or reply to accounts and, under certain conditions, send private direct messages, or DMs, to other Twitter users.

LinkedIn is more of a public/private network hybrid. There is a lot of information publicly available but most of your opportunities to engage with an account tend to happen after you’ve made a mutual connection on the platform through.

I like to think of these various engagement types on both platforms as existing on a spectrum based on how high the expectation of reciprocation may be from the receiver.

For Twitter you have Tweet level engagements such as likes and Retweets on one end of the spectrum. These are lightweight engagement types with essentially zero expectation of reciprocation- literally “one way” in design. On the other end of the spectrum is something like an @mention where there is a very high expectation of a reciprocal engagement. A follow is probably sits somewhere in the middle.

LinkedIn engagements like invitations to connect or join groups, InMails (LinkedIn’s messaging system) and introduction requests all have high expectations of reciprocity built in. There are an increasing number of lighter-weight engagement types available as LinkedIn ramps up more of its publishing features through LinkedIn Pulse, their long form, blog style publishing platform.

How and when to engage on Twitter & LinkedIn

I like to consider two key questions on how and when to engage with a prospect on Twitter or LinkedIn:

  1. How much real world or social context does the potential recipient about you? If none, start to build that context with lightweight engagements like likes and Retweets before coming on strong with a direct @mention. If this is someone you’ve met before, say at a conference or online discussion, then a more direct approach is likely appropriate.
  2. How does the potential recipient use the given platform? On LinkedIn, are they connected with a large number of other users or do they have a very sparse network (eg maybe just current and former coworkers). An invitation to connect out of the blue may not be well received if the recipients account is a real world rolodex, but would be totally appropriate if you see that your prospect is a power networker on the platform. On Twitter, is the potential prospect a total wallflower or mixing it up with other users on the regular? Are they Tweeting professional content or family pictures and sports commentary?

One big caveat is that you shouldn’t be totally over thinking the approach and on-going engagement. The main point is just that you don’t want to default to aggressive, in-your-face engagement out of the gate.

Notifications types on Twitter & LinkedIn

Let’s consider what happens when you engage on Twitter and Facebook. Both Twitter and LinkedIn send email, web and push notifications that are triggered by the inbound engagement that an account may receive. The type and frequency of notifications will vary based on the recipient’s account settings.

Here are some of the engagement based notifications that a Twitter user may receive based on network activity:

  • Your Tweets receive a like.
  • Your Twitter account receives a new follower.
  • Your Tweets are Retweeted.
  • Your Twitter account receives a reply or @mention.
  • Your Twitter account receives a new direct message (DM).

And, here are the notifications that LinkedIn may send you based on activity on your account:

  • Comment received on your post.
  • Invitation to join a group.
  • Invitations to connect.
  • Endorsement received.
  • InMails and Introduction requests.

The content and structure of these notifications is largely controlled by the platform. But, it is a good idea to familiarize yourself with what types of information is included in engagement notifications so that you can ensure that your account is properly merchandised to take advantage of the opportunity to influence the recipients decision to reciprocate where appropriate.

Final thoughts

If all else fails, just remember that people who are active on social networks like Twitter and LinkedIn want to receive engagement. So, give it to them. Just use the same good judgement you’d use in any professional setting when determining exactly what the right approach may be.

Two alternatives to the Alexa top 1 million website list

My favorite type of lead enrichment data is:

  • Insightful.
  • Cheap (or free!) to access at scale.
  • Available in bulk formats like CSV export or API.
  • Consistently and reliably updated.

Website popularity/rank is a great example of a piece of data that checks all these boxes. Comparing this data across prospects is a great way to quickly qualify or disqualify a large number of prospects. Selling to the long tail? Focus on leads that register in the bottom third of the list or not at all. Focused on the mid market? Remove the top third and so on. Its a very simple yet extremely insightful signal.

Alexa, a division of Amazon that tracks a panel of millions of web users to determine the popularity of websites, has long been the canonical free source of website rank data and available in a CSV download that is updated daily. But, late last month (November 2016) the company announced that they would no longer be publishing the the daily list of top million sites. Going forward, the data would only be available for a fee.

Then, after some disappointed feedback from various Alexa fans, the company reversed course and relaunched the free daily update of top million sites with this Tweet:

It is still unclear what the long term plan is for this list, but seems somewhat likely that a paid only future is in the cards.

Luckily, there are two free alternatives for a daily update of the top million sites. One has been at it for a while and the other has launched to address the presumed gap left by Alexa’s uncertain future.

Majestic is a search engine optimization tools company that began publishing the “Majestic Million” as a daily CSV download back in 2012. This list is the top one million sites on the web ranked by the number of referring subnets and IP addresses. The company explains that:

“A subnet is a bit complex – but to a layman it is basically anything within an IP range, ignoring the last three digits of the IP number”

I think of it as a directional proxy for the number of links on the Internet that are point to a given website (though that is likely a woeful over-simplification if not downright inaccurate!). Here is a direct download link for the latest file (note: clicking this link will initiate a 1M row CSV download).

Cisco announced just this week the launch of the “Cisco Umbrella 1M” list. This ranking is based on data culled from Cisco’s broad network of DNS and other tools. More detail on the data form the company’s announcement blog post:

The data itself is based on the Umbrella global network of more than 100 Billion requests per day, across 65 million unique active users, in more than 165 countries. Although the data source is quite different from Alexa’s, we believe it’s arguably more accurate as it’s not based on only HTTP requests from users with browser additions.

Here is a download page for Cisco data.

If you aren’t already using web ranking data in your lead scoring programs, I’d highly recommend you consider tapping in to one or both of these sources of data and give it a try.

How to build a Twitter content curation machine with @Zapier, @Feedly & @Buffer

Curating content on Twitter is a great way to stay on top of trends in your industry, educate your followers and build influence. But, it can be a lot of work to discover, format and publish content consistently.

Below I’ll describe the process that I use to discover and curate content for for my Twitter feed. It uses Zapier, a killer web service automation tool, to connect Feedly, Buffer and Twitter. It’ll will send any blog post that I save in Feedly and any Tweet that I like on Twitter to a Buffer queue. I do some light editing of the content before it is automatically scheduled by Buffer to be Tweeted out.

There are ways to completely automate this type of curation, but there are many downsides to that approach from my perspective. In general, I think the output of 100% automated tools looks completely automated (read: low quality). My main objective for the curation that I do is to stay on top of key trends in the industry I work in. I’m genuinely interested in these topics and the exposure makes me better at my day job (e.g. finding inspiration for new techniques, discovering new vendors, etc). So, complete automation completely misses the point for me.

I prefer a “cyborg” strategy that mixes some significant amounts of automation mixed with reasonable human intervention to ensure quality control.

There are several steps below, but the setup is extremely easy thanks to Zapier. The ongoing maintenance is also manageable. It takes me about 3 or 4 hours per week and costs about $35 per month all-in to keep this running.


  • Zapier Basic account: $20 per month. Zapier offers a free plan, but it won’t give you enough tasks to make this work well.
  • Twitter account: Free
  • Feedly Pro account: $65 per year. Feedly offers a free plan, but you’ll need to upgrade to Pro in order to take advantage of Zapier integration.
  • Buffer Awesome plan account: $10 per month. Buffer offers a free plan, but you’ll quickly run out of space in your buffer queue.

The setup

  1. Signup for your Zapier Basic, Twitter, Feedly Pro and Buffer Awesome accounts if you don’t already have them. I highly recommend installing the mobile Feedly and Buffer apps as well.
  2. Add your Twitter account to your Buffer account. This will allow you to publish Tweets from Buffer to Twitter.
  3. Add some blog feeds to your Feedly account. Feedly has a great feed discovery tool. You can also add individual feeds or upload an OPML file.
  4. Login to Zapier and click “Make a Zap!” at the top of the page.
  5. You’ll be prompted to select a “trigger” app. Select Feedly and then select “New Articles Saved for Later” as your trigger. You’ll be prompted to connect your Feedly account to your Zapier account. Once that is complete, you’ll be able to test that the integration is working as expected.
  6. Next you’ll add your “action” app. Choose Buffer and then select “Add to Buffer” as your action. You’ll be prompted to connect your Buffer account to your Zapier account. Once that is complete you’ll be prompted to create a template for the content that you send to your Buffer account. Here is how I have template setup:Screen Shot 2016-12-13 at 8.44.04 PMThis configuration will send the title of the post, the post URL and an image from the post directly to your Buffer. You can experiment with adding other elements, like author name and keywords, to the template if you like. Once you’ve completed the template setup you’ll be walked through a process of making sure everything works as expected.
  7. Name your zap and turn it on then click the “Make another Zap”. You’ll be prompted to select a “trigger” app.
  8. Select Twitter and then select “Liked Tweet” as your trigger. You’ll be prompted to connect your Twitter account to your Zapier account. Once that is complete, you’ll be prompted to enter a Twitter user name. Enter the name of the Twitter account that you’ll be using to curate content.
  9. Next you’ll add your “action” app. You’ll add Buffer just as you did in your previous zap. Once that is complete you’ll be prompted to create a template for the content that you send to your Buffer account. Here is how I have template setup:Screen Shot 2016-12-13 at 9.11.07 PMThis configuration will send the content of the Tweet that you liked and the @handle of the Tweeter to your Buffer queue. Once you’ve completed the template setup you’ll be walked through a process of making sure everything works as expected.
  10. Once again, name your zap and turn it on. You’re all done with the setup process! Now any Feedly article that you save for later and any Tweet that you like will automatically be sent to your Buffer queue.

Ongoing maintenance

I tend to save and like content each morning during my commute. It usually takes me about 20 minutes per weekday morning to work through new Feedly items and discover interesting content Tweeted by the accounts I’m following.

The content that hits Buffer needs some more attention before you start publishing to your Twitter account. It’ll be the raw material that you’ll use to create awesome Tweets.

Once per week, usually on Sunday afternoon, I edit enough raw Tweets in my Buffer queue to cover what I plan to publish the following week. I publish three tweets per week day, two on Saturday and one on Sunday. It takes me about an hour to edit the raw content into publishable Tweets. The number of Tweets that you have to format will depend on how frequently that you publish new Tweets. You can infinitely configure your posting schedule in Buffer.

I like to follow a simple Tweet structure:

  • Post title or relevant point from post. For example, a key stat or snippet from the blog post.
  • @mention of source. The original source will often like and Retweet my Tweet. I also change any company names to @mentions for the same reason.
  • Relevant hashtags. These will help people that follow certain industry or topical hashtags and keywords discover your content.

So, a Tweet for this blog post would look something like this:

“How to build a Twitter content curation machine with @Zapier, @Feedly & @Buffer via @leadscoring #contentmarketing #socialselling”

Make it your own

This setup is endlessly customizable thanks to the power of Zapier and the other tools used here. This works for me, but make it your own and customize to make it fit your content curation objectives.

Buried Treasure: Tokenizing email addresses for better lead segmentation

B2B lead generation programs are often centered around capturing an email address. It is common for marketers to segment email addresses based on domain for deliverability tracking. But, there is often deeper insight into lead type and quality to be derived from further interrogation of the components that make up an email address.

An email address can be split into at least three component parts:

  • The username
  • The website domain (also called the second level domain)
  • The website domain extension (also called the top level domain or TLD)

Each of these components has the ability to give you standalone insights that may not be readily apparent when you look at a submitted email address in its entirety.

The Username

The username is the portion of the email address that comes before the “@”. It is probably the most useful portion of the email address to analyze because it is so signal rich due to the amount of variation. Interestingly, it is probably also the least commonly analyzed component. Here are some common username structures:

  • Proper first name or proper first name and last initial like “joe@” or “joes@”. Email addresses with these usernames generally belong to employees at small companies or start ups. In some cases, these also may belong to very senior or tenured employees at bigger companies.
  • Proper first name and last name or first initial and last name like “jsmith@” or “joesmith@”. These types of usernames are most common for corporate email users at bigger companies that have developed standardization.
  • Any mixture of first and last name, initials or other words and a number “joes1977@”. These types of usernames rarely belong to corporate users.
  • A business or entity name like “joesbusiness@”. This username structure is common among very small businesses that may not have a dedicated website due to budget or knowledge limitations. Freelancers and independent consults will also use these types of usernames. That said, the advent of Google Apps and other solutions that make it very easy to set up a custom email domain without a great deal of technical knowledge required and low cost have made this less and less common.
  • Role based accounts like “marketing@”, “finance@” or “webmaster@”. These types of usernames can be a gold mine of insights as they can help you understand the lens under which an email lead may be analyzing your product. In other cases, role based usernames are too generic to be insightful.

Gmail users can add a “+” and additional text at the end of their username as a real time tagging mechanism. This looks something like “joesmith+word@”. Parsing out the content after the “+” can be extremely informational. For example, if a subscriber to your email list adds “+spam” to their username then you have a pretty good sense what their first impression of your website, list or service may have been! I’ve also seen the “+” used to segment out different clients or initiatives as in the case of “+marketing” or “+billing”.

The Domain

The domain is the portion of the email address that comes after the “@” and before the “.”.

  • Free email domains. The most common free email providers in the United States are generally Gmail, Yahoo, Hotmail (plus legacy variants MSN and Live), Aol and Comcast. But, there are many, many free email providers worldwide. Here is a list of thousands global free email providers as a reference.
  • Unique email domains like “joesbusiness.com”. These are typically the most common domain types in B2B lead generation campaigns.

There is really very little advanced signal you can get from a free email domain other than the fact that the user is not using a unique/corporate email domain. The quality of leads with free email domains is typically much lower on average than those leads that provide an email address with unique domain. But, that is certainly not a universal truth and you should look at your own historical customer data to determine how predictive email domain type may be.

Once you have parsed the domain out from the email addresses you can easily map back the underlying organization to third party data sets. This may help give you even more insight into the overall value of the lead. For example, you can match the email domain to Quantcast or Alexa traffic data, evaluate the technologies used on that domain using a service like Builtwithor Datanyze, or use a service like SEMrush or Adbeat to get a sense of the ad budgets of the company. You can also look at domain frequency across your inbound lead population. Are you seeing multiple email addresses with the same corporate email domain? This could be a great signal of interest from a specific company.

You will also often find that unique domains are an exact match to social accounts for the associated individual or business. For example, a contact’s personal domain “joesmith” matches their Facebook username or Twitter handle. There is plenty of room for false positives, particularly with very common names or words. But this type of domain to social account matching works well as a quick and dirty approach. There are many services such as Fullcontact.com or Clearbit.com that can expand email addresses to social accounts and other contact data if you are looking for a higher accuracy approach.

The Extension

The extension, or top level domain, is the portion of the email address that comes after the “.” (or after the first “.” In the case of international domain extensions).

  • TLDs like com, .co, net, org, biz, info
  • edu, mil, gov
  • Country coded TLDs like “co.uk” or “ca”

The most common business domain extension is .com. I’d guess that >80% of the high value leads I’ve ever processed were business domains with a .com TLD. Your mileage will certainly vary based on your target customer organization and region. If you sell to educational institutions or are a government focused vendor then the .edu or .gov extensions will be full of signal for you.

ICANN, which is the governing body of domain extension standards, has allowed for the release of hundreds of “generic” extensions, or gTLDs, over the last few years. As the name suggest, these are generally descriptive terms like .travel or .education. These types of generic domains have not generally had great adoption in the past. But it is worth noting that they exist as there is potential for a lot of signal to be wrapped up in gTLDs.

Find the Patterns

As with most lead evaluation techniques, the most important step is benchmarking your historical data to know what to look for in analyzing email tokens. Look for trends (perhaps by running a regression in Excel) in your existing customer base or historical lead win/loss data to get a better sense of which of these signals may or may not be important for your business.

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