Built to Wow: An Introduction to Launching Personalization At Your Company

The promise of personalization is enticing: a complete 1-to-1 experience for every customer, driven by every detail and data point about that person: who they are, their interests, needs and history. Their customer experience is completely optimized to deliver the right content at the right time, influencing brand engagement, purchase activity and “wow”-worthy customer experiences. […]

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The promise of personalization is enticing: a complete 1-to-1 experience for every customer, driven by every detail and data point about that person: who they are, their interests, needs and history. Their customer experience is completely optimized to deliver the right content at the right time, influencing brand engagement, purchase activity and “wow”-worthy customer experiences.

For years, this vision has been a pipedream among marketers, product managers and customer experience professionals. Many clients come to us wanting to “do personalization” but face significant challenges in doing so.

Part of this is due to the fact that “personalization” is so ill-defined.

At Brooks Bell, we define personalization as any experience that is delivered to a user based on known data about that person. By that definition, personalization exists on a spectrum: it can be one-to-few, one-to-many, or one-to-one. In the digital environment, product recommendations, customized search results and even segmented experiences are all considered examples of personalization.

But while many companies are already implementing these experiences, there’s still an overwhelming sense that many brands have yet to arrive in terms of personalization.


Got a bunch of burning questions about personalization? Submit them using the form below.

We’ll use this information to make sure we cover these topics in our upcoming posts.


A 2018 study of 300 marketers by Evergage and Researchscape International found that 98% of respondents believe personalization helps advance customer relationships, but only 12% were “very” or “extremely” satisfied with the level of personalization in their marketing efforts.

This is because (not unlike experimentation) personalization is a business strategy that should evolve in order to deliver long-term value. And while it’s true that many brands already have the ability to do personalization, they’ve also found that elevating and scaling a personalization program is difficult, costly and, frankly, can feel pretty darn impossible.

So, how to do this? In addition to the fundamentals for a standard optimization program, there are three critical working components that need to be established for personalization:

  • Technology: you need top-notch tools to centralize user profiles and deliver personalized experiences;
  • Data: personalization requires a clean, unified view of relevant customer attributes, and
  • Strategy: you need research and planning to purposefully and effectively launch, scale and benefit from personalization.

In the coming weeks, we’re going to break down personalization further by each of these components. We’ll outline the best practices, advice, strategies and tips to go from scrappy to smart when it comes to introducing and scaling personalization at your organization.

Struggling to execute a scalable personalization strategy? We can help. Contact us to schedule a free 30-minute consultation.

The post Built to Wow: An Introduction to Launching Personalization At Your Company appeared first on Brooks Bell.

Back to basics: Measuring your social media efforts with unique acquisition channels

Segregating paid, organic and social activity in analytics clarifies the activity that drives which type of conversion.

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Most organizations are spending a considerable amount of money and resources on their social media marketing efforts. These efforts generally take the form of three types of effort – organic, paid and promoted (also referred to as owned, paid and earned). No matter how you label them, you should segregate them into three unique marketing acquisition channels in your analytics reports to correctly evaluate how effective your efforts are.

To segregate traffic driven to your site from various social media properties, you’ll need to configure custom channels in your analytics tool. (For a detailed explanation on how to do this in GA, see the Marketing Land article The Google Analytics Social channel is broken. Here’s how to fix it.

Defining custom social channels

Before starting any configuration changes, first decide not only the names of these new channels, but what they represent for your clients (both internal and external).

I’d recommend setting up the following three channels.

Paid social: Consists of any paid ads you are running on any social media property to drive traffic to your website.

Promoted social: All activity performed by your social media team where no additional marketing fees are required. Typical activities that fall under this channel include typical posting to your social media channels.

Organic social: Any activity that the general public (people not on your payroll) drive traffic to your site from social media. This includes a person clicking on a “Share This” icon on your blog post or perhaps just including a link to your site in a spontaneous social media post.

Once you’ve defined your social media channels, you need to define the medium definitions (for GA the utm_medium parameter value) to be used your generate a custom URL to track (see Google URL Builder). The great news is you don’t need to do anything for organic social.

Here are some typical medium definitions (required by your analytics software) or make up your own. Note you can use more than one to refine your analysis at a later date.

Paid social: Paid-social, Social-PPC, Social-CPC, Social-display, Promoted-post

Promoted social: Psocial, Promoted, Post, Tweet

Remember, these changes to your analytics tool are permanent and will remain in place unless deleted. They will not impact historical data.

Repeating the benefits of custom channels

With this additional information, you’ll be more effective at evaluating which content is performing best and you’ll be able to compare its performance across the organic, paid and promoted social channels.

 

Another advantage is it will be much easier to compare conversion rates and goal achievement between different channels. In this example, a Data Studio report was created to showcase different goal conversions by all defined channels.

It is only by segregating paid from organic from promoted social activity that a complete picture of which activity drives which type of conversion. From the above chart, the Paid Search channel generated the most contact forms being submitted, while social (organic) and paid social drove zero forms being submitted. In this case, it’s important to look further into your analytics reports for assisted conversions (does a site visit generated from Paid Social come back to the site later through another channel) to determine the influence of Paid Social on contact forms being completed or other conversion points.

Any questions?

I hope you found this useful, and hope you’re as thrilled as I was to be able to segregate my client’s social traffic into meaningful refined channels. We are now able to put a true value on all our social marketing efforts (paid or promoted) and to calculate a realistic ROI which makes all business owners happy.

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AdStage launches Join to automatically unify campaign, analytics, sales data in one dashboard

Customers will have full-funnel visibility into how their search and social campaigns are driving sales outcomes.

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Source: AdStage. An example of leads data available in AdStage Join.

Does this scenario sound familiar? Marketing rejoices in all the leads it sent to sales. Sales grumbles that too many of the leads were garbage. Animosity and bitterness fester until the two teams function more like competitors rather than like a unit working toward the same goal. If you’ve worked in a B2B-oriented business for any length of time, this is a story you’ve likely heard before.

To help shift this paradigm and help align sales and marketing teams, AdStage launched Join on Tuesday.

What problem is it trying to solve? The San Francisco-based campaign reporting and automation startup’s new product pairs sales and marketing data in one dashboard. AdStage Join launches in response to what the company sees as a “macro movement” toward addressing the need for marketing and sales alignment.

“At the very least, [sales and marketing] need to be sharing data if not working directly together,” said AdStage co-founder and CEO Sahil Jain in an interview last week. “Only the most sophisticated organizations are doing this, and they have to do it manually in Excel. That’s time intensive and error-prone.” Additionally, Jain said, most of these efforts only get to the campaign level.

To give marketers the full view of how their campaigns perform for the sales team, Join brings together campaign data from search and social channels such as Google, Bing, Facebook and LinkedIn, on-site behavioral data from Google Analytics and lead and sales data from Salesforce.

How does it work? Join automatically maps sales and campaign data together, without the need for URL rewrites. As illustrated in the screenshot above, advertisers can see cross-channel campaign data from both Google Analytics and Salesforce all in one view. Marketers can then drill down to the keyword level for optimization insights.

Jain stressed this is not a multi-touch attribution product: “Maybe one day we’ll get there, but for now we’re just connecting the data.” If you’re using Bizible, for example, AdStage brings in that already attributed data. Join can also be used with AdStage’s other products. For example, an advertisers could set rules for Facebook campaigns in Automate based on sales data it sees in Join.

AdStage Join, is the fourth in its suite, which also includes an analytics product called Report and campaign automation solution Automate, along with the AdStage Data API.

Who is the target customer? Join is aimed primarily at providing a solution for B2B focused, lead generation advertisers. Jain says the current customer base is fairly evenly split between agencies and direct clients. “This is a new tool for agencies to go beyond top of funnel for clients and be held to a higher standard,” said Jain.

Digital agency 3Q Digital has been using Join in beta for roughly 6 weeks. CEO David Rodnitzky said optimizing campaigns based on sales data had been a painful challenge prior to the agency’s adoption of Join, noting that connecting ad data to Salesforce saves staffers time and provides critical information.

Why you should care. Join surfaces data from each step of the funnel — from ad impression and click to lead and revenue — across search and social channels in one dashboard. Bringing data sources together in a frictionless way could save marketers buckets of analysis time and help the sales and marketing teams work more more efficiently together toward shared goals. AdStage says it now sees more than $900 million in ad spend annually on its platform.

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Using data responsibly doesn’t have to weaken marketing strategies

In today’s diverse marketplace, businesses need data solutions that empower them to anticipate and respond to many circumstances and challenges.

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Data privacy is, as it should be, high on the minds of tech companies and the public at large. Unfortunately, much of the discussion of late has centered around controversies originating with the misuse or fraudulent nature of some data sources. But we shouldn’t let this cloud our collective judgment about how data can help businesses make better decisions.

When processes and strategies are in place to ensure the gathering and use of data is done responsibly, we can do right by consumers and brands. The benefits and opportunities made possible with accurate, well organized and actionable data will benefit the entire industry.

Brands must put data privacy at the forefront

Recently I was honored to speak at the Responsible AI/DI Summit where I addressed these issues and clarified the importance of brands ensuring that their consumer data strategies are a top priority. Brands have a responsibility to be forthright about the types of data they have access to, the permissible uses of that data and the value that data can provide. Developing data strategies that are useful but respectful to consumers must be at the forefront of every business today.

Brands are under tremendous pressure to make quick and important decisions based on data, but they shouldn’t lose sight of the trust that is placed in them and their partners to be transparent about what data is being used, how it will be used and how it will be gathered. And, with a supercomputer in every consumer’s pocket, data is available at a rate never seen before. When combined with the processing power to make sense of it, businesses can make smart, responsible use of the latest in AI technology to target and segment their audiences with strategies that prove to be a pragmatic approach to reaching their current and even new customers. Though consumers today remain weary of how brands are using their data, they are also more willing to engage with trusted brands who handle their information responsibly and provide more tailored and customized experiences. According to Accenture, 92 percent of U.S. consumers believe it’s extremely important for companies to safeguard their information, though 44 percent of U.S. consumers are frustrated when companies fail to deliver relevant and customized experiences.

Balancing trust with providing personalized experiences is something that any retailer handling consumer data today must understand as a business imperative.

Healthy approaches to data framework

To reach the full potential with the aid of data, businesses must also adhere to a healthy approach that accurately weighs the authenticity and quality of data available. Before data can be applied to business decisions, it must be refined, analyzed and measured against specific business challenges.

Once data is ingested and stored, it is critical for enterprises to remove low-quality data and refine the remaining data into usable, contextualized data sets that can be applied to analyze a number of key business challenges. Raw, unfiltered data will lead to confusion. But data that is scored, screened, filtered and then contextualized can be leveraged for high-level analysis that will reflect optimum levels of confidence for an organization and its partners.

Data should empower confident business decisions

Mobile location data is among the most rich and impactful datasets available today and when businesses analyze it effectively and responsibly they can compare different opportunities, such as prospective store locations, product localization strategies and holiday promotions.

In 2018, with Amazon knocking on every retailer’s front door with a commanding share of the ecommerce market, the strategies put in place to gain a competitive advantage should without a doubt include a thoughtful marketing strategy that encompasses responsible data practices.

Businesses of all types should embrace the use of data and be focused in their approach. Don’t let a few bad apples or outright nefarious examples of data manipulation cause you to miss out on this opportunity. Understanding the benefits and challenges of data is key, and the sooner enterprises understand this dynamic the better. In today’s diverse marketplace, businesses need data solutions that empower them to anticipate and respond to many circumstances and challenges.

The types and lasting effect of decisions that enterprises must make are expanding and if a leader doesn’t have all the available information to make those decisions it can hurt their business and customers. If you aren’t considering all the options and ways in which data can help you, I strongly encourage you to embrace the challenge and learn how the responsible use of data can reinforce your principles and help your business grow.

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Did the data-driven era miss an exit?

If the focus is on the right data aligned to business strategies instead of the same basic demographics, marketers don’t have to live in fear that inaccurate data will derail campaigns.

The post Did the data-driven era miss an exit? appeared first on Marketing Land.

people crossing in crosswalk

According to headlines, martech embodies technical sophistication, touting thousands of companies fueled by sumptuous features like artificial intelligence, virtual reality, personalization and more. Yet, a recent study found that what marketers really want is more, high-quality demographic data. I can’t help but think, did the data-driven era miss an exit?

The modern marketer can use thousands of pieces of consumer information — demographics, purchases, hobbies, social activity, geolocation etc.—but many marketing efforts are still based on the same basic demographics of age, gender and income. The status quo may be considered the easier, more risk-averse route. But if we stay in autopilot, marketers will slowly lose speed, falling behind for failure to embrace new technology in the spirit of innovation.

Time for an oil change of our way of thinking

First of all, I don’t propose we do away with demographic data, as it is incredibly powerful. But it only represents a sliver of the information available about a person. Furthermore, the accuracy of demographic data is already in question, and the cost of its poor quality can add up for marketers.

If a marketer over-relies on only a few demographic data points when defining an audience, accuracy of those specific data points is mission critical. But with a more comprehensive approach to defining an audience, where thousands of data points are considered, no single data point is at risk of toppling the operation.

No junkers, no hidden gems

There are hundreds of data aggregators in the martech ecosystem, specializing in CPG, behavioral, online, offline data and more, and many claim theirs is higher quality than others. These claims should make marketers wary. For example, I recently read an article claiming online purchase data is the ideal source of truth because it’s tied to a tangible transaction. But for a retailer that wants to drive new, incremental purchases, an advertisement targeted to someone who already bought is not ideal. In this instance, the quality of the behavioral data is a moot point because it doesn’t align with the retailer’s objectives. Further, when marketers have thousands of data points at their disposal, it seems risky to put so much weight into a single point.

Get into gear

Too often marketers question accuracy and quality before knowing what they want to achieve. Take, for example, a TV manufacturer that wants to find new customers. Using recent online purchases, even if the data is 100 percent accurate, won’t find many new customers. Would an audience of men that’s 100 percent accurate fair much better? Or an audience of people who live within a 5-mile radius of an electronics store?

Accuracy is important. But an audience with perfect accuracy that isn’t tied to campaign objectives won’t drive performance.

What if, instead, the manufacturer considered past purchases as one piece of the puzzle — a way to group its valuable customers. Then it could consider the thousands of additional data points available about those customers to find the commonalities that comprehensively represent the ideal customer. This audience mitigates the risk that a single data point’s accuracy will negate performance, considers all relevant data points, and bases the audience on the goal of driving purchases.

Who’s behind the wheel

With the right data aligned to strategies and in concert with business outcomes, marketers don’t have to live in fear that inaccurate data will derail campaigns.

When it comes to performance, it’s not just about data accuracy, but comprehension, recency, longevity, frequency, scalability and more. Once marketers are able to consider all of the data at their disposal, the martech industry can get back on track to the destination that the data-driven era promised, one where data drives smarter, one-to-one decisions that improve efficiency and results.

This story first appeared on MarTech Today. For more on marketing technology, click here.

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Who’s Hiring in November?

Here are our picks: Sr. Analytics Manager – Experimentation – Ebates.com is looking for a “creative problem solver with a passion for delivering data-driven insight and has experience in leveraging Testing and Experimentation framework to improve customer experience” in San Francisco. Marketing Analyst- Growth Analytics – In Atlanta, Georgia, Pandora is looking for a candidate […]

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Here are our picks:

Sr. Analytics Manager – Experimentation – Ebates.com is looking for a “creative problem solver with a passion for delivering data-driven insight and has experience in leveraging Testing and Experimentation framework to improve customer experience” in San Francisco.

Marketing Analyst- Growth Analytics – In Atlanta, Georgia, Pandora is looking for a candidate to “assist the Marketing Analytics group’s analysis efforts around customer targeting, acquisition, and retention; campaign, audience and subscription forecasting, and KPI tracking as Marketing Analytics works in conjunction with broader Finance, Product, Engineering and Data Science teams.”

Product Manager, Data & Analytics – Join The Walt Disney Company in New York and lead the “analytics-related product development efforts.” “Provide strong input into data tech R&D and data-related critical initiatives, and work on the integration activities with Disney Streaming Services’ analytics technology partners.”

Marketing Analytics Analyst/Data Scientist – The Children’s Place is looking for an analyst to be “responsible for supporting the company’s efforts to create a strong and advanced analytics team focusing on our customer” in Secaucus, New Jersey.

Ecommerce Product Manager – Boxy Charm is looking for a candidate to join their team in Pembroke Pines, Florida to “work with stakeholders across the business to understand needs and build requirements to create and maintain a roadmap for transforming our customers’ experience.”

Executive Director, Chief Marketing Officer – Lenovo in Chicago is looking for a leader to “generate revenue by increasing sales through successful marketing for the entire organization, by driving global marketing and communication, advertising, Public Relations, digital and social media.”

If you are looking to fill a position, give us a shout and we’ll add it to the next careers blog post.

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Unlock multi-touch attribution with CRM campaign tracking

If you’re using a CRM to house leads then you likely have the campaign tracking tools for middle funnel activity even if you have an offline transaction point.

The post Unlock multi-touch attribution with CRM campaign tracking appeared first on Marketing Land.

display chart graphic
Image credit: www.Curata.com

Brands with an offline transaction point often struggle to measure the full customer journey from acquisition source through to revenue. Often times, if revenue can be attributed back to something, it’s to the marketing channel responsible for the lead. This measurement is usually implemented with either a first or last touch attribution model for channel attribution and completely leaves out the rest of the customer journey.

The missing visibility and measurement is post lead acquisition. Once a lead enters our systems, how do we measure the effectiveness of our campaigns and lead treatments? Even better, how do we attribute revenue to content pieces and treatments applied to that lead in-funnel?

The answer may be something we already have access to. If you’re using a CRM to house leads then you likely have the tools to track middle of funnel activity at your fingertips with Campaign Tracking.

What is campaign tracking?

Campaign tracking within a CRM is technically an entity or object that tracks a variety of information about an event, mailing, emailing, or other marketing initiatives. It’s basically a container that houses all of the components of a campaign across channels and treatments.
Leads and contacts can be members of one or more CRM campaigns allowing visibility into the effectiveness of both single and multiple campaign influence across all levels of our funnel from lead to cash.

campaign graphic
Image credit: www.Salesforce.com

What are the benefits of CRM campaign tracking?

Depending on the CRM and how it has been architected and implemented, campaign tracking provides a significantly deeper level of insights and measurement including the ability to

  • Tie marketing activities to our sales pipeline
  • Compare the effectiveness of different marketing initiatives and their influence on each other
  • Measure mid-funnel activities alongside marketing channel attribution
  • Measure the effectiveness of content post lead acquisition
  • Inform the sales team of historical marketing activities via the contact record
  • Roll-up similar lead sources into a single object
  • Connect online & offline activities
  • Enable holistic ROI reporting
  • Preserve data integrity & maintain hygiene
  • Enables multi-touch attribution modeling within your funnel

Attribution and CRM campaign tracking

Now that measurement is enabled at such a granular level in-funnel we can see marketing activity influence across the funnel from lead to customer. This is where attribution really gets complex! Similar to the first-touch, last-touch, multi-touch debates on marketing channel attribution. Now we have these same debates in-funnel when attributing back to campaigns within our CRM.

Do we give credit to the campaign that initially acquired the lead?

Do we give credit to the campaign the lead responded to before they converted to an opportunity?

Do we give credit to the campaign that influenced the lead right before they converted to a customer?

First-touch attribution model

First-touch is pretty self-explanatory. In this attribution model, all credit is given to the very first action taken by the user that created the lead record.

attribute graphic
Images credit: www.Curata.com

The first-touch attribution has its advantages, it’s super easy to implement. The lead is tagged using a custom field and that field rides on the record all the way through the funnel to closed won. However, this model leaves so much of the story out neglecting to consider all other interactions the user had or actions the user took beyond that initial entry into the database.

Last-touch attribution model

Last-touch attribution is the opposite of first-touch. Instead of giving all credit to the first action the user took, we’re giving it to the last step the user took. Also easy to implement by merely over-riding that custom field.

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Last-touch is fantastic for measuring the effectiveness of campaigns targeting the bottom of the funnel geared directly toward driving a purchase decision. However, if we only look at what ultimately turned into a sale, we really lack insights into what levers to pull to get them to that point and we are leaving a ton of opportunity on the table. We are also boxing ourselves into diminishing returns and expensive tactics and are unable to scale our marketing programs.

Multi-touch attribution model

Multi-touch models are more complex, recording all interactions and giving credit to all touch points in the journey. They provide the clearest picture of attribution and provide the most insights regarding what levers to pull across the funnel to improve velocity and efficiency of our marketing investments. To implement a multi-touch attribution model within your funnel you have to utilize CRM campaign tracking. This is the biggest benefit of the campaign tracking tools within your CRM.

CRM campaign tracking reports

Once campaign tracking is properly set up and working within your CRM and when used in conjunction with a clean and granular lead source strategy, CRM campaign tracking opens up rich and robust reporting options. Your data will tell a very different story!

Here are a few sample reports that can be generated when both campaign tracking and a clean and granular lead source strategy are applied within Salesforce.

display graphic chart

I’d love to hear how you are utilizing campaign tracking within your CRM and what kind of new insights you’ve been able to pull. My guess is that once you were able to get to this level of insights, marketing resources were moved around to concentrate on what you didn’t even know was working within your marketing program.

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Measure Your Success

Business management consultant Peter Drucker is often attributed with the saying “you can’t manage what you can’t measure.” By this he meant that you don’t know whether you’re succeeding unless your goal is defined and tracked. When it comes to DMO websites there are six goals we see tracked more often than others. They are:… Read More

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Business management consultant Peter Drucker is often attributed with the saying “you can’t manage what you can’t measure.” By this he meant that you don’t know whether you’re succeeding unless your goal is defined and tracked.

When it comes to DMO websites there are six goals we see tracked more often than others. They are:

  • eNewsletter SignUp
  • Visitor Guide Download
  • Aggregate Bounce Rate
  • Aggregate Time On Site
  • Aggregate Goal Conversion Rate
  • Aggregate Pages Per Visit

Because it is the most commonly tracked, we covered eNewsletter Sign-up in more detail in this previous post. In this post, we’ll pull from our report State of Personalization for Destination Marketers, so you can see how you measure up to your peers.

In the below charts, the Non-Targeted numbers represent website visitors who were not served personalized content. If you are not serving personalized content, you should compare your own performance against this group.

If you are serving personalized content, you will be in the higher performing group and should compare your performance to that of the website visitors tracked under Targeted.

How does your website compare to your peers on these key metrics? Does this bring up questions about what you’re measuring and managing? A simple but well organized measurement strategy is critical to managing a successful website. If you have any questions about best practices, please feel free to contact the Bound team here, and we’ll be happy to chat.

If you would like to download the  Free Guide: State of Personalization 2018 Report from which we pulled these metrics, click here. In the report, you will learn how destination marketers like you are leveraging:

  •      Website personalization benchmark statistics
  •      Strategies for implementing personalization
  •      2018 trends in content and personalization
  •      Real case studies from successful destinations

Related Posts

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How data visualizations enhance Executive decision making

Just as Michelangelo approached that giant block of Carrara marble and said, “I saw the angel in the marble and…Read blog postabout:How data visualizations enhance Executive decision making
The post How data visualizations enhance Executive decision …

Just as Michelangelo approached that giant block of Carrara marble and said, “I saw the angel in the marble and...Read blog postabout:How data visualizations enhance Executive decision making

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