The Modern Customer Funnel

Originally, businesses created a traditional sales funnel where the company was in control and got to push the prospect through the sales grinder. That original model is dead now that a new model has emerged. The main difference in the new model is that instead of businesses working toward a “close,” both customers and businesses alike are starting to see the funnel as the beginning of a deep and valuable relationship with each other. The new model was coined Pirate Metrics by Dave McClure because of its infamous acronym: AARRR! This stands for the five key metrics that McClure believes map out the lifecycle of the customer: Acquisition, Activation, Retention, Referral and Revenue.

AIDA vs. AARRR

The original AIDA model has been around in the marketing world for ages. The lifecycle went like this:

A is for Awareness, or attracting the customers’ attention.

I is for getting the Interest of the customer.

D is for getting the customer to Desire your product and convincing them it will satisfy their needs.

A is for Action, which is leading customers toward the actual purchase.

While its principles still have some value, it is now pretty out of date. The main difference between AIDA and AARRR is that McClure’s followers start with acquisition of customers instead of Awareness building, according to Sean Ellis. From there, it goes on to extend the life of the client-relationship with the retention phase.

Data Driven Analysis and The Funnel

Consumers don’t follow a linear path through the funnel any longer. Much of the journey relies on digital engagement. For instance, consumers often check out product reviews on websites and across platforms, look at their social media accounts and then make purchases online. All of this information is tracked and available for us to analyze. The split-funnel attribution model takes advantage of this data-driven insight into how each part of the funnel boosts conversions by tracking impressions, clicks and conversion info. In turn, this data-driven analysis helps you to create more personalized content that drives acquisitions, leads and revenue as well.

The Acquisition Phase

In the new marketing funnel, you place a lot of emphasis on your first contact point with your customer. Your initial marketing efforts worked and you have their attention. They’ve probably visited your website and some of them have even taken an interest in your content. These numbers serve as the starting point for analyzing which of your marketing channels are working. You can see which types of content are holding people on your site and which ones are trickling down and out. Breaking this into stages helps, such as who signed up for your mailing list, who signed up for your Beta list and how long their engagement with certain aspects of your site was. The ones who are subscribing are the ones in an advanced stage of acquisition – these are the ones you want to push forward with your Activation steps.

Retention Phase

In today’s connected world, the conversation doesn’t end when the sale is ‘closed’. For example, Halloween is confined to sales during September and October. However, the conversation doesn’t abruptly stop after the 31st. Technology allows for companies to have a continuous conversation with customers, make them continuously feel appreciated, and increase their lifetime value as a customer.

Traditionally, it was hard to monitor when customers were talking about a brand and required more resources to focus on retention vs. customer acquisition. In the modern era, we have technology such as Oracle’s new image recognition software designed for brands to ‘listen’ for when customer post photos including recognizable brand attributes. These tools make it easier to focus on increasing the lifetime value of customers through engagement with the intention of increasing their individual net promoter score as well.

 

Sources

https://www.ensighten.com/company/newsroom/lets-split-funnel/

https://www.convertwithcontent.com/the-content-marketing-sales-funnel/

https://twitter.com/seanellis/status/629699744097439745

http://www.samuelhulick.com/life-inside-dave-mcclures-pirate-metrics-funnel/

People Data

Data driven companies look at a broad range of information to optimize everything from their business processes to their digital marketing. They use people data to gain an understanding of their audience and how best to segment them in a digital age. When you use this data in your digital marketing efforts, you create a more relevant and personalized experience. Janrain found 85 percent of companies used personalization techniques to improve the customer experience. You can use people data to differentiate yourself from your competitors, but you need to understand how to effectively implement this data into your digital marketing campaigns.

Context from Identity vs. Attributes

Context matters significantly in your marketing efforts, and you gain many contextual clues from a person’s identity versus their attributes. Someone’s identity is who they are, and this remains consistent throughout the marketing process. The person’s identity never changes, but their attributes change based on context, such as going from the office to their home or switching from a desktop channel to a mobile channel. When you know the buyer’s context, you can optimize your marketing strategies.

Difference Between B2B and B2C Data

People data in B2B and B2C marketing display several differences. Buyer motivation is one significant area where B2C and B2B data differs. Hubspot found B2B buyers focus on efficiency and company expertise, while B2C buyers are on the lookout for deals. You have a longer buying cycle for most B2B purchasing decisions, and you’re rarely dealing with only one decision maker. Your B2C and B2B marketing efforts both benefit from people data, but you approach each market in very different ways.

Personas and Audience Segments

People data helps you identify audience segments and create buyer personas. While these two terms are sometimes used interchangeably, they represent two distinct concepts. An audience segment describes a group of potential customers you focus on, such as Chief Information Officers at technology startup companies. You identify broad characteristics of this market, such as their general demographics and pain points. You create buyer personas to make an in depth profile of people or groups that are close to making a purchase decision. You look at the challenges they face, the customer’s story and pain points unique to that persona. Typically, you lean on audience segments for your top of funnel marketing efforts and deploy buyer personas for the middle and end stages.

When you effectively implement people data into your marketing efforts, you can use a data driven approach to pinpoint what your customers want. As content personalization becomes the default expectation for buyers, you need to put your people data to good use in order to better serve your clients and your competitive positioning.

Sources:

http://www1.janrain.com/rs/janrain/images/Industry-Research-Unlock-Customer-Data.pdf

http://blog.hubspot.com/agency/differences-b2c-b2b-marketing

Unstructured, Structured and Standardized Data

Have you ever accidentally put an object in the wrong place and get frustrated when you can’t find the object later on? The function of data repositories and information systems, are to store large quantities of data in the right place, so it can be easily accessed at a later date. The aim is to make the formatting consistent across systems so that different types of data are compatible with each other. Usually, systems will have data models in place that lay out the structure, manipulation and other aspects of the stored data in order to define and format the data to make it more accessible. These types of data are usually separated into three categories: structured, unstructured and standardized.

Structured Data

Structured data is the easiest type to capture and organize in a data model. This is data that lives in a fixed field within a file, like information you would find in a spreadsheet. In order to store structured data, you have to define which fields of data you are planning to store and organize it into rows and columns. An example of this is keeping a database of clients along with names, dates, addresses, currency and so forth. It also may involve restricting the data input in certain ways, such as number of characters or drop-down menus.

The advantage of structured data is that it can be easily entered, stored, searched and analyzed. Data like this is usually managed using a Structured Query Language (SQL). When data isn’t properly structured, it can mean that you’re missing out on some big marketing and advertising opportunities – which we’ll get to in a minute.

Unstructured Data

Unstructured data refers to the information that doesn’t live in straightforward rows and columns. This information is a little more complex and can’t usually be stored in tidy fields. It includes things like email messages, text documents, social posts, photos, videos, web pages and other kinds of documents. The information within these files might be organized, but the data still doesn’t fit into a database in a logical way. Studies have shown that between 80 to 90 percent of data in any company is unstructured – and this number is continuing to grow!

Because so much of every company’s data tends to be unstructured, it makes sense that businesses want to find ways to use this information to make better decisions. The issue is that it’s hard to analyze unstructured data. That’s why a number of different software solutions have been developed in order to try to sort through unstructured data in order to find important information that businesses can use in order to stay competitive.

Standardized Data

Standardized data is data that has been received in various formats and then transformed to a common format that makes it easier to compare the two. This helps make many types of data crisp, clear and easily accessible. For instance, if you have a field for street names, and some people write North Main Street while others write N. Main St., you could standardize the fields to be N. or S. and Street or St. It’s a way of making the data fit more neatly into fields so that search queries can be run more effectively.

Why Are They Important?

Businesses in every industry are scrambling to compile and measure more and more data every day. Structured data can offer vital information about customer interactions and consumer behavior that can help translate into increased sales if dealt with in the right way. Processing unstructured data is, arguably, even more important, but it does present some challenges. Text-based information sources like email, social media interactions and mobile data can often go completely ignored because it’s difficult to compile and analyze. However, this unstructured data can tell us a lot about the customer journey and give us powerful insights into buying habits.

How to Analyze Unstructured Data

There are a number of different, non-traditional ways to analyze unstructured data. Companies can review conversations on social media and analyze customer interactions in call centers or in-house, and then find ways to record them in a structured format. You can also set up automated processes to capture data, such as tools that monitor social media sites or RSS feeds. Figure out which areas are of interest to your customers, and organize this information into relevant categories. In this way, you can work toward standardizing the data to make it easy to compare it with structured data to identify trends and patterns.

What Does This Mean for Marketing?

Social data is powerful for driving your content marketing strategy, as it helps you understand what content to create and how much weight to give each type of content within your plan. You can use metrics from Facebook Insights, for example, to see how well different types of posts are performing. Other tools, like Optimal Social, can offer structured data on what types of content your readers are engaging with.

Another important use of structured data is to boost your search engine rankings. Web crawlers are now trolling sites to look for specific items and keywords, and also to verify that you have high-quality content on your site and are a company that deserves to pop up in user searches. This kind of rich data markup helps Google understand what your content means, not just what it is saying. Google analytics and other site analytics can help you optimize your site and your online content so that Google picks it up first.

About Diggen, Inc.

Diggen is a data marketplace to help marketers become and manage data driven enterprises. Data driven marketing initiatives accelerate growth, since it improves key performance indicator (KPI) metrics and increases revenue over 19%. However, marketers have monumental technical challenges accessing data assets, sourcing data providers, and integrating into their marketing technology stack.

 

Our platform uniquely combines a data marketplace to source all marketing data with middleware to integrate into all marketing technology stacks. For example use our intuitive web interface to append gender, age, location to email addresses and integrate into an email service provider. Therefore, marketers segment their audience for newsletter emails, which creates relevancy, more engagement, and increases conversions.

 

Visit Diggen at http://www.diggen.com.

 

Sources:

  1. http://www.innovatingstuff.com/2012/12/03/structured-and-standardized-data-sources/

  2. http://acumenmd.com/blog/human-condition-structured-unstructured-data/

  3. http://www.webopedia.com/TERM/S/structured_data.html

  4. http://www.webopedia.com/TERM/U/unstructured_data.html

  5. http://digitalmarketingmagazine.co.uk/digital-marketing-data/how-understanding-unstructured-data-is-useful-for-customer-insight/2198

http://www.npws.net/blog/how-structured-data-can-enhance-your-online-marketing

Using Identity and Attribute Data For More Effective Marketing Initiatives

Broadcast marketing is dead. Sending the same message to everyone of your customers is less effective every year.

A more effective approach is to build campaigns to a select a group of your customers. You can do that with accurate identity and attribute data about your clients:

  • Identity data is the primary data about your customers — for example: name, address, phone and email address.
  • Attribute data is more detailed data like their age, income, gender and education.

With better information, you can identify what will appeal to specific customers and create more relevant promotional messages to meet their needs. Let’s take a closer look at identity data and attribute data.

Identity Data Points

Identity data refers to data points you can use to identify one customer from another. Every media channel in some way uses identity data. Smart phones have specific device IDs. Internet browsers utilize cookies to ID users. Retailers and online platforms routinely use e-mail addresses as identity data.

Once you have identity data about different clients, you can customize your promotional messages for very specific audiences, rather than using a broad message which may only appeal to a finite segment of your client base.

All Phases of the Marketing Funnel

Identity data is prominent in many phases of advertising, marketing and digital analytics. Brands use it throughout their marketing funnel. Online publishers and media routinely check their site metrics and visitors using identity data.

There are many forms of identity data. Low-level data like cookie IDs identify web browsers, but don’t provide a lot of information about your clients. E-mail addresses, in contrast, span several media channels, tend not to change much, and are usually specific to an individual person. That’s why progressive marketers want to collect and utilize stable data points.

Attribute Data Adds Depth

In a previous article we discussed the Differences In Data sourced for marketing initiatives. There are also different types of attributes accessible for marketing purposes, such as demographic, geographic, interest, and behavioral.

Gender, age and income are all examples of attribute data. This is demographic information that provides more complex and actionable information about your customer. It can include things like whether they are a premium or regular customer.

Attribute data is used in creating, developing and implementing marketing and promotional efforts. Examples of this include:

  • Encouraging members that have passed the two-year membership to sign up for the premium membership level.
  • Targeting specific product deals to customers that have bought similar products in the past.
  • Segmenting product promotions by market depending on weather conditions.

Eliminate Noise and Inefficiency

Each of these data points provide leverage that has not been available in the past. Now marketers can reach customers with more effective messaging that provides more value to them. It not only features products and services they want, it eliminates the noise of anointing broadcast marketing which hits many people outside the target market.

Cross Channel Optimization

This is becomes more complex as customers interact with your business across a variety of channels. Let’s say one of your customers opens an email, later searches for your product online, asks for opinions from friends on Facebook, or they watch a YouTube video about it. A profile of this customer spans across multiple channels to provide unified information which is powerful for marketers. There are a variety of technology solutions to support the complexity of identifying, tracking, and matching users across multiple channels.

You can segment your audience to target users more effectively. The data is anonymous so privacy is respected. But you can get a view across multiple channels which changes marketing. You want to be able to build campaigns that reaches clients across channels, understands their behavior and segments their message.

Data Collection Mechanisms

The question then becomes do you have the right mechanisms to collect this data. And do you know how you’re going to utilize it after you’ve gathered it?

The secret is to get the clearest picture of your target customer as soon as you can. The challenge is that the data is constantly changing. People move, get new email addresses, and change their phone number.

Using the proper data is critical to ensure the effectiveness of every direct mail piece, email message or retargeting campaign you initiate. The only way these efforts work is if you have accurate data that you keep up to date.

Transparency and Trust

You can gather more information, and more accurate information if you communicate to your clients and prospects how their data will be used. A recent Gigya study showed that a large majority of respondents will click out of online registrations because they feel concerns about how their information will be used.

It’s important to address these concerns because accurate information is key to effective messaging. That’s why some online platforms like Facebook have introduced line by line permissions in their sign-up process. This is the practice of asking several questions after login that allow customers to decide how their information will be used.

Building and developing a relationship with your customer is crucial for long term success, so transparency and trust are core values to your marketing initiatives. It is mutually beneficial to the customer and marketer, so both gain value in the relationship.

More Effective Messaging

It’s important to collect accurate identity and attribute data not only because you want to reach the consumers who are open to your message, but you want to improve the quality of the message itself. You are the bridge between your customer’s data and the message that will most resonate with them.

Your goal is to look for stories in the data that you can pull out and frame so that it motivates your clients to take action. The trick is to make it personable and memorable for the market segment you are targeting.

Win Clients Over with Storytelling

For example, Buffer, a social media sharing company, shares the story of a customer support app called Groove. Groove was able to generate a 300 percent increase in the people that read a particular post using the power of storytelling. They explain how using dialogue, metaphors, emotions, familiarity, and powerful graphics combined to drive a huge response.

Art and Science of Data Collection

Identity and attribute data are the science. Your creative and storytelling abilities are the art. Effective marketers are adept at both. Gather accurate data, look at it to see patterns, and build stories that will create the most impact from your target market.

About Diggen, Inc.

Diggen is a data marketplace to help marketers become and manage data driven enterprises. Data driven marketing initiatives accelerate growth, since it improves key performance indicator (KPI) metrics and increases revenue over 19%. However, marketers have monumental technical challenges accessing data assets, sourcing data providers, and integrating into their marketing technology stack.

Our platform uniquely combines a data marketplace to source all marketing data with middleware to integrate into all marketing technology stacks. For example use our intuitive web interface to append gender, age, location to email addresses and integrate into an email service provider. Therefore, marketers segment their audience for newsletter emails, which creates relevancy, more engagement, and increases conversions.