Targeting. Retargeting. Firmographic… demographic... behavioral… psychographic... targeting.
We see more and more technologies and techniques to reach a target audience emerge, seemingly by the minute.
The crossover between these different options is becoming overwhelming – how are they the same, how are they different, and how should a demand generation marketer figure out which ones to use?
I set out to bring some order to this mish-mosh of targeting options that demand generation marketers have today. And here’s what I got (so far).
Why has targeting become all the rage?
While there at least a dozen solid reasons, here are four I see driving it:
1. Content marketing best practices are demanding it
As companies build personas and target strategies to specific roles and verticals, the next logical step is to build programs that reach those target audiences in the most efficient way.
2. Email isn’t enough
Email is just one marketing channel and has significant limitations, the biggest one being that you can only email those you have in your database. Additional marketing channels are required beyond email to reach new audiences, extend your reach and meet demand generation requirements.
3. Closed loop marketing systems optimize for effectiveness
As marketers build closed loop marketing systems, they can hone in on the elements of what makes their most effective marketing investments. This drives the insights that feedback additional targeting requirements to make future investments more effective.
4. Vendor innovation
VC investments in marketing technologies continue to grow -- many of the companies mentioned in this article have received significant investments as they look to capture their share of the marketing budget.
What are the different ways to target?
I have split these out as five techniques to reach an external audience, three techniques to target visitors on your website and then a final emerging category all to itself.
1. Retargeting Via Cookie
How it’s done: Visitors to a website are cookied and then targeted with banner ads as they visit other sites.
Advantages: Tend to be cost effective compared to other techniques.
Disadvantages: Limited to those who have already visited your website, so it’s really a method of conversion optimization and not reaching a net new audience.
- Bizo - Display Ad Retargeting
- Google – Remarketing via Google AdWords
- AdRoll – Display Ad Retargeting via ad network, Facebook & Twitter
2. Targeting Specific Database of Prospects, through Publishers
How it’s done: Provide the publisher with your prospect database and then target programs to those specific individuals.
Advantages: Can supplement active nurturing programs to laser target those participating in nurture streams with additional content impressions in a credible context – reach your audience where “they spend their time.”
Disadvantages: Limited only to those only in your database, so it’s a method of enhanced nurturing not reaching a net new audience.
I could not find specific examples but I have to believe publishers today are offering this by requesting “house databases” from marketers; in addition I wonder if any of the social networks allow for this 1:1 targeting. If you are aware of specific offerings that fit this profile, please share that info in the comments section and I’ll update
3. Targeting via Demographic (e.g. Vertical)
How it’s done: Marketer provides target information and programs focus in specifically on those targets to take best advantage of spend.
Advantages: Now we are getting to the sweet spot of this list where the targeting capabilities should offer significant advantages to marketers.
Disadvantages: Not so much a disadvantage, but if leveraging display ads you will need to invest in message/creative for the display ads and the content for the landing page conversion to maximize the effectiveness of these investments.
- Bizo – Targeted Display Ads by Demographic Data including job function, industry and title. These typically incorporate the notion of real-time bidding to make the ad buys as efficient as possible.
- Bizo – Social Ad Targeting including title, seniority, industry, company size
- LinkedIn – Advertise directly on LinkedIn with targeting by job title, function, industry, company size and seniority
- Madison Logic – Vertical targeted publisher programs including contextual ad placements, dedicated email blasts, keyword search, research directories & LinkedIn groups
4. Targeting Via Named Account
How it’s done: Supply a specific named account list to a publisher, and run programs directly to that set of companies.
Advantages: Phenomenal way to align with sales programs by targeting to the specific accounts sales is going after and supporting outbound efforts – so for example we have a outbound calling/email program targeting the same named accounts supported by targeted display ads to those accounts – integrated with a capital I!
Disadvantages: I haven’t seen these programs offered with a role-based targeting overlay, so they tend to target via company and some level of page content but not guaranteed to be reaching the right roles within your segmentation.
- DemandBase – Account Targeted Advertising
- Bizo – Display Ads by Target Accounts
- Madison Logic – Named account leads whereby marketers name the specific companies for their programs to target
5. Targeting via Contextual Content
How it’s done: Targeting an audience based on contextually relevant content, Google has been doing this for years with ads through their content/display network, and now the latest fad has evolved to distributing blog & article content via a similar manner.
Advantages: Can be a cost effective way to reach a new, relevant audience. In the case of the contextual content promotion, it provides a means to grow traffic to supplement traditional SEO efforts.
Disadvantages: Google’s content network has long been plagued with quality issues, and that same issues applies to contextual content promotion. Marketers can grow their traffic but is it above your quality bar?
- Google’s Display Network – banner ads based on page content
- Reactor Media – editorial posts as “you might also like” boxes based on contextually relevant content
- Outbrain – contextual content promotion via publishers through
On Your Website
6. Targeting Anonymous Visitors by Industry or Company
How it’s done: These companies have mapped IP addresses to companies and then categorized those businesses by industry to allow for real-time targeting of content by industry or other company based demographics such as revenue.
Advantages: For a first-time visitor without even being cookie or registered on your site, content relevance by industry can lead to significantly higher engagement and conversion.
Disadvantages: Not so much a disadvantage but a challenge – requires close work with content creators to ensure the right industry-specific content exists to leverage these capabilities. You can create industry-specific versions of your website – messaging, case studies, content and offers all industry specific.
- Marketo Real-Time Personalization (formerly Insightera) – Website Personalization by Industry of Company for Anonymous Website Visitors
- Demandbase - Website Personalization by Company
7. Targeting Known Visitors
How it’s done: This requires a personalization engine to be directly connected to the marketing automation platform holding the lead specific data. So for example, if you had customers identified and wanted to communicate with them a certain way on the website. The possibilities are endless.
Advantages: Truly powerful, only limitation I suppose is that you need to have the individuals cookied via your marketing automation which means having them click an email from you or fill out a form to get the cookie down.
Disadvantages: Again, not so much a disadvantage but with all the possibilities need to have strong internal know-how to prioritize what you are trying to accomplish and manage it.
- Marketo Real-Time Personalization (formerly Insightera and now referred to by Marketo as "RTP") – Individual personalization based on lead record data from the Marketo Lead Management platform. RTP syncs this data to enable real-time personalized website content based on that known lead’s data. (I confirmed this with David Myers, the Product Manager for RTP).
8. Behavioral Targeting
How it’s done: An engine which collects history of click patterns by prospects and connects it to at least one outcome (e.g. Page View, MQL, Opportunity) to then determine relevant related content or next action for future site visitors
Advantages: Can be a powerful addition to a website to drive engagement based on past data
Disadvantages: Behavioral targeting based on past click patterns (e.g. most popular next content from past visitors to a specific piece of content) does not connect the viewing of that content to a positive outcome, so the most effective engines will also factor in attaining a marketing goal such as MQL or Opportunity.
- Marketo Real-Time Personalization (formerly Insightera) – This can be accomplished both with the content recommendation engine as well as leveraging the RTP platform for targeting rules. For example a targeting rule could be based on behavioral segmetns e.g. clicks, visits, referral, search term or specific page visits - powerful stuff.
- Evergage – Also Website Personalization- although hard to tell exactly how they do it from their website and what the targeting is based on - need to learn more about these guys.
- I’m sure there are more out there but I can’t place any right now, so this is another area where I’d welcome feedback
Predictive Lead Scoring
9. Predictive Targeting aka “Predictive Lead Scoring”
How it’s done: Such a hot topic that I gave it a category all to itself, these “big data” vendors are collecting some aforementioned data (marketing automation, CRM, website) and coupling that with additional data sources including product usage logs, customer support history and social websites to then predict high probability qualified leads for targeting purposes. At that point, what happens? Most likely the data is then fed into a marketing automation tool to trigger a campaign or program to target that lead or in some cases these vendors own web personalization engine to target web content based on these predictive models.
Advantages: Instead of guessing at a lead scoring model which ultimately misses many key factors, the promise of these systems is achieve the benefits of lead scoring to your demand generation without the pain and hassle of building your own model.
Disadvantages: If these leads are being handed off to Sales or Teleprospecting team, need to build confidence in the “black box” so that these predictive scored leads are pursued with the same belief in the leads as others.
Examples: These companies are all “talking the talk” and at the same time SiriusDecisions is seeing adoption of these technologies accelerating.
- Lattice Engines
- LeadSpace - This is one to watch in particular as from my initial review they appear to do the best job of identifying targets outside of your existing database
Conclusions & key takeaways
Having sifted through this, three key points stand out:
#1 – Options are plentiful, consider your needs and choose wisely
The more integrated your solutions, the more you will be able to ensure you are managing a closed loop system with clear measurement and reporting. It’s okay to use multiple platforms but where you can, standardize on a smaller set of vendors, and ensure you have a marketing automation platform which can serve as the hub of your targeting tools.
#2 - Marketo Real Time Personalization stands out as an emerging player
Looking at the options for web personalization in this way helped show the true potential of Marketo’s Real-Time Personalization platform, formerly Insightera. Tying web personalization to the Marketo database can be a truly unique capability, and on-site behavioral targeting based on content consumption is another area where Marketo can stand out.
#3 - Predictive Lead Scoring will become a must-have for mature marketing automation users
I don’t love the name, but when you consider that these companies can serve as an engine incorporating many of these aforementioned targeting criteria – web history, content consumption, demographic data plus purchase data, product data and social media – the possibilities are powerful. One of the questions I intend to explore here is understanding how these vendors enable targeting actions – is the standard to simply feed information back to marketing automation that indicates the lead is a key target, or do the capabilities extend beyond that? It may turn out the predictive lead scoring systems only specialize in the data processing and predictive targeting, and that information then feeds into the targeting mechanisms we’ve outlined here.
This is a rapidly evolving space, so please leave additional ideas, comments or corrections via feedback, and I’ll continue to update this post with the latest information.