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    Why Content Marketing Strategies Fail Without Predictive Analytics [Podcast Recap]

    As per a recent survey by Content Marketing Institute’s & MarketingProfs, nearly 22% of B2B marketers said their content marketing strategies weren’t very effective while 4% of the respondent revealed their content marketing efforts weren’t effective at all.


    If this sounds familiar to you, you need to rethink your content marketing strategies.

    Sean Zinsmeister, Senior Director of Product Marketing at Infer, recommends implementing intelligent models to content marketing strategy in order to achieve tangible benefits.

    In a recent interview with Atomic Reach, he shared some key insights on content marketing for small businesses.

    Why Content Marketing Fails?

    Sean attributes the failure in content marketing to poor decision making process by small businesses.

    Here are couple of reasons why your content marketing isn’t working.

    1. You’re Following an American Idol Marketing Model [37:15]

    According to Sean, most small businesses follow the American Idol kind of marketing model where they generate a lot of buzz around their product and attract attentions from people that are never going to buy from their products.

    Social media platforms and their followers have both evolved significantly. It’s not about hiring a dedicated social manager for your social media campaign anymore. In order for your brand to resonate with your followers, day in and day out, you need to establish a personal connection.

    Here are a couple of things that you can do:

    • Find a way to solve your audience’s problems.
    • Bring in your content marketing manager or product manager and let them create content to engage with your audience.
    • Share your expertise with your audience and solve their problems.
    2. You’re Taking Downstream Metrics on Their Face Value [21:20]

    Moreover, many content marketers tend to fall into the trap of downstream metrics, e.g., the number of downloads. Making decision purely on downstream metrics may lead to unfavorable outcomes because you tend to drive your resources in the wrong direction.

    However, predictive analytics helps you differentiate between actual buyers versus downloaders and find out good leads based on which you can better target your buyers.

    “Predictive analytics is about optimizing your decision making. It’s about making smarter decisions and reaching the right buyers with a more personalized message in order to influence their buying decisions.”


    3. You’re Sitting on the Fence Ignoring Opportunity Cost [23:00]

    Sean says that opportunity is everything. If you’re going to keep on driving your resources in the wrong direction for too long, you’re going to run out of steam soon and give up on your marketing efforts.

    Therefore, having a data-driven and analytical approach is imperative to the success of your marketing efforts.

    “Content is a craft and it takes time to build that quality in the content. If you’re not 100% sure if it’s going to resonate with your audience, then it could be a very big risk in terms of creating the wrong message that is not going to be a good fit for your audience.”

    When you look at the data sets with predictive analytics, it helps you find answers to two most important questions:

    • What are the patterns here?
    • Now that I understand patterns, what should be my next strategy?

    According to Sean, answering these two questions is the very foundation of Predictive Analytics. It helps your confidence and decision-making with regards to content marketing strategies.

    Success = Content Marketing + Predictive Analytics [19:00]

    When it comes to content marketing, Sean strongly believes in the power of predictive analytics.

    Predictive analytics is essentially a sophisticated and scientific approach to analyzing content marketing metrics in order to predict behavioral patterns of your prospects and optimize your marketing efforts for optimum results.


    By combining metrics from data mining, statistics, behavioral modelling, machine learning and third-party datasets, predictive analytics offers immense insights to help you make better decisions in your content marketing efforts.

    “What was in that content that made it more popular? How do we then take that content and build other pieces from that eBook; maybe, we do a video, infographic et cetera to amplify that message and reach more potential buyers.”

    When you know the likely outcome of your future content marketing efforts, you’re in a better position to reduce your marketing cost and boost your conversion rates.

    Smart Marketing Moves with Predictive Analytics [21:00]

    As a content marketer, you should be able to generate good leads that have a high chance of conversion. While this sounds pretty simple in theory, many content marketers fail to separate the wheat from the chaff.


    The problem with conventional analytics is that it can lead you to inaccurate interpretations. For example, a higher number of eBook downloads doesn’t necessarily mean many of them will ask for a price quote or place an order.

    However, when you use predictive analytics with your content marketing efforts, you go deeper and establish the intent of the people that downloaded your eBooks.

    This helps you channelize your efforts on the potential buyers, make your content marketing strategies more productive and boost your conversion rate.

    In short, with predictive analytics tools, you get huge bang for your buck.

    How Predictive Analytics Help Your Performance: Case Studies [24:30]

    Does predictive analytics really work in real-life?

    Sean shares some case studies where businesses have immensely benefited from predictive analytics tools.

    Case Study #1: Shore Tel

    Before adopting predictive analytics tools, it’d take a frontline rep at Shor Tel about a hundred calls to generate one marketing-qualified lead. After adding predictive analytics tools, they realized ‘A’ leads were actually converting at 50%. As a result, they went to from hundred calls per MQL to 12!

    In other words, they saw their call volume drop by 88% which was a massive productivity gain. So, the reps started focusing more on buyers that were more likely to buy from them, which lead to a higher conversion rate and revenue gains.

    Case Study #2: Social Tables

    Social Tables, the Washington-based company had a large number of leads but the conversion rate wasn’t good enough. They used predictive analytics and profiling which allowed them to hyper-segment and personalize the message, which eventually helped them to create more relevant content for their target prospects. As a result, their monthly revenue increased by $5,00,000 per month.

    But, it’s More than Just Boosting Your Productivity [30:45]

    The interesting things about applying a predictive model to content marketing is that it will show signals which businesses could use to create content for a particular segment of prospects.

    For example, if you’re selling software to your customers, the predictive analytics tool can say if you’ve been able to sell well to a particular type of prospects, e.g., companies with less than 500 employees or using a particular type of technology.

    This will help you personalize your message for a specific segment and boost your conversion rate.

    Adoption Rate of Predictive Marketing Tools [34:00]

    Predictive marketing is relatively new in the IT and software industry and, Sean says, even though it’s still in the nascent stage, the trend is heading upwards.

    The potential users of predictive analytics include technology companies especially in the sales and marketing industry. Moreover, the other potential candidates who can benefit from predictive analytics tools are front-line marketing reps who want to boost their performance and productivity. Predictive modelling can also be very effective tool for content marketers.

    Sean believes more and more companies need to be educated about the potential benefits of predictive analytics to increase the adoption rate in the sales and marketing industry.

    The Bottom line

    As the content marketing space gets more crowded and competitive, content marketers must learn how to use their limited resources and craft meaningful stories that resonate with the highly potential buyers. In a such scenario, predictive analytics is going to play a key role for sales and marketing professionals in the technology industry.

    What do you think about predictive modelling? Has your company already deployed predictive analytics into their content marketing strategies? What results have you seen so far? Please, let us know in the comments below.


    About the Podcast Host & Author:

    Podcast Host: Amanda is the Marketing Coordinator at Atomic Reach, writing posts, sharing news, and connecting with the community on the daily. Her attempts at clearing her ever-growing reading list continues to be unsuccessful, and she really does believe that sharing is caring.

    Author: Susanta Sahoo is founder and chief content marketing strategist at Top League Technologies, a digital marketing start-up in Bhubaneswar, India. By offering SEO consulting services, he helps SMB’s build their online presence and boost ROI. Follow him on Twitter:@sushantsahoo

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    Topics: Sales & Marketing, artificial intelligence, big data, buyer behavior, case studies, consumer behavior, Content Marketing Strategy, data and marketing, marketing, marketing metrics, marketing performance, marketing technology, martech, podcast, podcasting, predictive analytics, sales, sales decisions, Technology, tracking