Are you connecting your marketing to business results?

I was at the Marketing Analytics Summit a few weeks back, and talked to a lot of people who felt that:

  1. Measurement was really important
  2. Measurement was really, really hard

The eternal struggle for marketers seems to be connecting marketing actions to business results. But this can’t be a reason to give up on analytics. 

Are you driving sales? Prove it.

Marketers know how important we are to the process, but we’re also the first to face budget cuts when things get rough if we can’t directly prove our worth.

At the end of the day, no matter what your marketing techniques are, if you aren’t able to measure results, do you even know if they mattered? How do you, as a marketer, demonstrate the value you’re adding to the organization?

“Data is now fundamental to how people work, and the most successful companies have integrated it into everyone’s daily workflow. Data is the new application.” Frank Bien, CEO and President of Looker, sums up this need beautifully. Without centering data, marketing can falter.

People with a deep analytics background might already get this, but it is surprising both how difficult analytics remains, and how some people still don’t get it. They figure “I drop a bunch of stuff at the top of the funnel, and then my job is done.” Okay. But wait a minute. What about the middle and the end of the funnel? We need to be asking how this stuff progresses.

And let’s make no mistake, this is hard. B2C attribution is difficult but usually attainable. B2B attribution not only has a significant data integration challenge but there are process, technology, and often cultural impediments to measuring B2B results. So how do you work on this? Well, technology may be able to help.

Data Science is the Future.

Our Senior Strategist Mike Moran advocates for marketers to also become data scientists. He notes that “A lot of marketers got into marketing as a refuge from math.” They maybe liked the creative side — creating great copy, imagery, telling a story. Don’t get me wrong — those things are important. But if you don’t know your numbers in 2019 and 2020 you’re not going to live for very long in this business.

Getting the right data was the goal five years ago. Companies hired Chief Data Officers taking their data wrangling games to the next level. The reality? It’s more complicated than that. It’s not the data, it’s what you do with the data. If you haven’t seen results yet it’s because you haven’t yet put that data to work.

And that’s where data science is today, figuring out ways to put the data to work. Using advanced technologies like natural language processing (NLP) to understand the content the website visitors are consuming and pairing that data with machine learning educated models of desired journey patterns can help marketing teams qualify prospects and help sales reps picking up MQL progress the deals.  

Because we’re years, if not decades, away from any form of general AI we’re going to have to continue to rely on specific models that help with very specific pain points in our process. There are many applications available today that operate within this sort of framework. It’s still important to be able to connect our marketing actions with measurable results. Some of these advanced capabilities make our ability to do so a little bit easier.

Interested in personalization with proven results? Check out our technology solutions.

Is your personalization for your visitors… or for you?

Let’s view personalization through your visitor’s eyes

Anyone who has kept up with me on just about any social media platforms knows I’m all about music, and my guilty pleasure – always – would be investing in a new guitar. Or, y’know, guitars. More is better. And if I were to visit a music store that collected data on visitors, they’d know I like a certain make of guitar (I do) and that, for example, I bought two last year and have only bought one so far this year. Maybe, the bright salesperson thinks, “this guy needs need another axe.” 

Poor personalization, which we see all the time, might recommend a guitar exactly like the ones I’ve already bought. Or just knowing I like “guitars” and recommending one that isn’t the right price point, lacks the right features, or doesn’t fit my needs. Or even worse, knows that there’s a warehouse full of unsold Gibsons and suggests a Gibson because that’s what “we need to sell.”

True, effective personalization on the other hand recommends a guitar maybe one level up from what I bought last time or that people just like me also own. It needs to take into account me. The real me. It knows my interests, my behaviors, my goals, my spending habits, and much, much more. But it understands me, not as a target or as a prospect. But as a human being. 

High-quality personalization requires two types of data

What differentiates good personalization is an understanding of your visitor and what their preferences are. These preferences can be explicit or implicit.

  1. Explicit: Explicit data reflects what individuals have told you about themselves. Maybe you bought syndicated research or you have first-party information that human beings gave you. Explicit data often doesn’t feel like merchandising because you’re simply reflecting the best product for their particular needs based on what they’ve told you.
  2. Implicit: Implicit data on the other hand comes from looking at your customers’ patterns of behavior and performing pattern matching, suggesting content and products based on their activity or the activities of others like them. This is how behavior based personalization works

Study your visitor’s behavior

In behavior based personalization, the behavior that’s being exhibited on the site leads us to believe the customer is trying to achieve a certain goal. Once we understand the goal, we can test to see if we’re right (I say “we” because content recommendation is what I do with SoloSegment.) We say, “Hey, here’s some recommended content that seems to match what you want. Does this help you progress your journey?” (Clearly, we’re not explicitly stating that out loud, but that’s essentially what the models are looking to understand). Even better, the model gets a little smarter every time, learns from customer behaviors, delivers another iteration – or iterations, in practice – and makes the experience better for the customer. You’d expect a good salesperson to do this naturally, right? So why not expect the same of your website… your 24/7/365 salesperson?

Again, this is all about understanding your customer’s goal. Personalized content recommendations make suggestions to a visitor about the best content they can check out next. If you have data about the topics customers are interested in, why not help keep them on topic? Why not help them find what they really want? And as the data helps you discern customer intent, move them towards their ultimate objective. Which, I should point out, is what you want anyway. 

What is your visitor’s goal?

“How can we sell these guitars in the warehouse?” I’m sorry to say, is usually not the right question. It’s not about “What are we trying to achieve?” The right question is “What is the customer trying to achieve?”

That understanding, that focus on customer objectives and helping customers progress along their journey is what truly differentiates good personalization from bad. And its utility goes even beyond that; the better you understand your customer, the better you can merchandise whatever it is you sell, whether it’s enterprise technology, financial services, or, y’know, electric guitars. In practice, it doesn’t even matter whether it’s B2C or B2B

What’s your customer’s goal? What data do you have about the customer? And did you use that data in ways that help them reach their goal? That’s not just great personalization. That’s music to my ears. 
Interested in what implicit, behavior based personalization can do to help you drive revenue for your business? Check out SoloSegment’s technology solutions right here.

The Deep Dive: What Does Content Marketing Need to Be?

Content marketing can be entertaining, helpful, or informative, or perhaps it can solve your audience’s problem. One good test of content marketing is whether it helps your audience even if they never buy your product or service. Here’s what content marketing needs to be to develop customer commitment.

Must Marketers be Data Scientists?

Big data is having big effects on content marketing, nowhere more than in its ability to make sense of the complexity of human language. Understanding data science is necessary for agile marketing in 2019. Here’s how marketers can utilize data to hone their craft.

What’s Inside Behavioral Data?

Personas have been used for a number of years by B2B digital marketers to craft content that aligns with a visitor’s context. But we all know that personas are also so… 2015. The rise in personalization has revealed both the limits and challenges of persona-based content creation — creating and maintaining content for every persona is a lot of work and getting that content in front of the visitor at the right time is tricky.

Keep Your Content from Disappearing into the Blogroll

Your content marketing is too valuable to waste

How findable is the content on your site? If the answer is that you aren’t sure — you may have a problem. And you aren’t alone. Many marketers spend great lengths of time on content marketing. But a lot of that content goes unread. The main problem is that the people you want to read it can’t find it.

What’s Wrong with Advertising: The Case for Data-Driven Content Marketing

As content marketing has been practiced today, it resembles custom publishing. Companies tell stories that romanticize their brand, distributing those stories through various channels and amplifying them through social media. Content marketing has come to be more akin to advertising.

Personalization — It’s Not Just for B2C

This past year, the demand for personalization is at an all-time high.

According to a Lytics white paper, two-thirds of customers want brands to adjust content based on their real-time context. Over 40% are annoyed if you don’t. And another two-thirds of those said they skip making a purchase out of annoyance.

That’s not just a problem for retail.