5 Challenges Brands and Marketing Agencies Face with Data in 2018

The rapid pace of technological innovation and the sudden emergence of Big Data has left a lot of marketers feeling left behind.  In less than a generation, the marketing industry has shifted in a way nearly unprecedented in its entire history.  It has gone from a largely intuitive or psychological art to being heavily defined by data, analysis, and science.

This has created numerous challenges for marketing agencies, both new and old.  Getting a handle on their data, using it properly, and finding new ways to reach out to consumers are challenges facing every marketer at work today.

What are some of the biggest problems faced by modern brands and marketing departments?  And what could potentially address those problems?  Here are some answers.

Problem 1:  Getting a Handle on Big Data

One of the biggest key challenges simply involves the collection, storage, and access to data.  Some organizations still find themselves struggling to get the information they need flowing in.  Others have opened too many pipelines, and find themselves drowning in an ocean of data without clear ways of organizing it.

In either case, what’s called for is a data-collection plan.  Don’t collect data for its own sake.  Have clear goals in mind for what the data will be used for, then act accordingly.  If you know what the data is for, it’ll be much easier to collect and sort it.  Be forward-thinking, and focus on laying the good groundwork now that will pay off in the future.

Problem 2: Market Disruptors

If there is an industry that existed prior to the 21st century, it’s probably now seeing digital disruptors arise and create large changes to that industry.  Retail is a perfect example:  Amazon is putting retailers out of business across the country, and even causing problems for some of the biggest names like Wal-Mart, yet Amazon has (almost) no physical stores.  Similar examples are arising constantly, such as the sudden boom of Uber and Lyft and their threat to traditional taxis, or the way Netflix is cutting into cable company profits.

The best solution here – if possible – is to become the disruptor.  Go on the offensive.  Read your data, look for trends, and ask “is there a digital solution to this problem?”  Look at processes related to your industry where a long-established solution exists, then think of a better one.  Re-invent the mousetrap.

If you don’t, someone else will.  Don’t be on the defensive.

Problem 3:  Consumer Distrust  

If there’s one problem with marketing that a lot of companies really don’t want to address, it’s this:  Most buyers and consumers don’t like us.  Some outright hate us.  Particularly when talking about younger buyers – those under 40 – there has never been an era when marketers have been more distrusted.  And that’s a BIG problem.

Much of this has to do with how much information the public now has about businesses and their day-to-day interactions with customers.  It’s easier than ever for buyers to learn of questionable behavior and organize themselves against it. Many have become so cynical that they simply distrust anything and everything that comes from marketing departments.

The solutions here are, broadly, twofold:  First, spend more time cultivating brand ambassadors online.  Find friends on social media, and YouTube, and other online outlets who genuinely support your product/services.  Word-of-mouth is more powerful than ever in this age where advertisements are seen as propaganda.  Use research and analytics to discover who your buyers trust, and get those people on your side.

The other solution is honesty.  When you must openly market, be as transparent as possible.  Cite sources.  Don’t overstate facts or capabilities.  Do not ever get caught in a lie.  It is possible to build consumer trust on a brand-by-brand basis, but that trust must be earned through trustworthy behavior.

Problem 4:  The Sales and Marketing Split

For too many decades, sales and marketing were treated as wholly separate entities within a business.  In worst case scenarios, they even had something of an adversarial relationship, with each tending to blame the other for failures.

This simply does not fly today.  Sales and marketing must be working hand-in-hand.  They need to know what each other is doing, and they need to be sharing data – particularly since each will likely have access to key insights the other lacks.  This is where a strong CRM-style solution can be extremely useful.  By centralizing data where both sales and marketing can access it, they can form closer links and develop initiatives jointly.

Better yet, get product development in on the data-sharing too.  In particular, this can eliminate the perennial problem of sales or marketing over-promising, and then getting stuck with a product which disappoints its buyers.  Use smart data sharing to keep sales, marketing, and/or R&D on the same page.

Problem 5: Security

If you’re keeping data, you have to keep it safe.  Unfortunately, as we’ve seen from many many headlines over the past few years, this is easier said than done.  It seems like hardly a month goes by without another high-profile name turning into a high-profile embarrassment due to data breaches, ransomware attacks, or other cyber-criminal activity.

Unfortunately, there’s no magic bullet solution here.  You simply have to be willing to spend the time and the money remaining abreast of the latest data security ideas and keeping your security systems up-to-date.  If management balks at the cost of updating security, remind them that -according to IBM- the average cost of a data breach is between $3 and $4 million dollars.  And it can be much higher.

The “it can’t happen to us” mentality has to be overcome because it can happen to anyone regardless of size.  Be prepared.

Always Keep Informed

If there’s one unifying factor in this, it’s simply that knowledge is power.  Both in terms of data and your own insights, keeping your eyes and ears open is the best way to ensure you’re aware of potential data challenges before they become major data problems.

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