Share on facebook
Share on linkedin
Share on twitter
Share on facebook
Share on linkedin
Share on twitter

4 Overlooked Questions You Need to Ask Before Creating a Data Strategy

The world is awash with data, of which 2.5 quintillion bytes are created every single day, and globally, 90 percent of all data was generated in the past two years.

This represents a huge opportunity for marketers, but it also brings challenges. Obtaining data is the easy part – the question now is how do you ensure that data is valuable and useful? How do you make sure it serves your business best by helping you formulate effective marketing campaigns?

Here are four essential questions that are usually overlooked, but should be asked before creating your data strategy, in order to make sure that your data is valuable and serves your business’ goals.


Q1: How Recent Is Your Data? 

Data recency is a key metric when building a data strategy. The more recent the data is, the more valuable it is, as it more closely reflects a consumer’s ever-changing behavior.

Using analytics tools, you can assign your customers a recency score based on their recent visit to your website and the interval of a purchase they recently made. This will help you filter out new users, for example, if that would be helpful for your marketing strategy.

This will help you target your marketing spend more effectively. If you are promoting your business daily to your customers, but most of them only visit once a month, that would be a huge waste of your marketing budget. That segment of the budget would be better spent targeting those customers who visit more frequently, or crafting a bespoke marketing strategy aimed at converting these less frequent visitors into more habitual customers.

Hence it is wise to refer to a recency score before launching any new campaigns. That way, you will avoid bombarding your customers with the same old marketing materials, and instead segment your audience into more highly targetable tiers.


Q2: How Noisy Is Your Data?

Not all data is created equal. Sometimes you can be faced with ‘noisy’ data – this is where some values or labels are wrong to some small degree. A few percentage points might not seem like a lot, but it is enough to corrupt or distort the data so it tells a very different story to the one told by the ‘true’ data. This can lead you to create a misguided marketing strategy.

In these instances, you need to look closely at other variables to see if you can leverage them to remove the noise. Another way of ironing out these wrinkles is to aggregate the data into a greater data set.

For example, in touchpoint data, one particular cookie might receive 100 display impressions in a row from the same website. In this instance, you must decide whether this is a blip and so should be treated as just one impression, or if there were actually 100 impressions in such a short space of time. It is worth bearing in mind such potential outliers, as – if undetected – they can wreak havoc when it comes time to analyze the data.


Q3: How Diverse Is Your Data? 

The more data sources you can use, and the more diverse those sources, the better. That is because data pulled from a wide range of diverse sources – as long as they are all relevant – will give you a more rounded picture of your customers’ habits and behaviors.

Using a single data source is a road to nowhere, as your data will be very limited. You can add extra dimensionality to your data by adding more sources, such as purchase history, customer profile information, search behavior (both on your site and on the wider web), and campaign data. This will let you analyze your marketing data in much greater detail, giving you more insights upon which to act.


Q4: How Fast Can You Feed New Data to Your Machine Learning Pipeline?

Machine learning is by far the quickest and most effective way of selecting useful data sets. However, machine learning – and any AI model in general – is only as good as the data you feed it. So, you should make sure you have satisfactory answers to the previous three questions before feeding data to your machine learning pipeline.

Then speed is of the essence. Otherwise, you create a bottleneck in the data lake, which will compromise the recency of the data, and hence its efficacy. It will be critical how quickly you can feed the data to your machine learning pipeline in order to test it out.

Flexibility and scalability (up as well as down) will also be crucial considerations when choosing a machine learning model. So make sure you pick one that will serve your business well as it evolves in the years to come. 

Data is invaluable in creating marketing strategies, but you need the right data, treated in the right way. By asking these four questions, you will drill down to the really useful data, generating the kind of actionable insights that are essential to develop an effective marketing strategy.


Let us know the marketing challenges that you’re facing, and how you want to improve your marketing strategy.


How to Build an Effective Multichannel Marketing Strategy

Brand websites, online ads, SMS, mail out… today’s enterprises can use more marketing channels than ever before. Multichannel marketing allows brands to leverage multiple channels to reach their customers more effectively.   What Is Multichannel Marketing? Multichannel marketing is the process of marketing to consumers through two or more channels simultaneously. These can be online (e.g. your branded website, app notifications, email, messenger, SMS, web push, social media, etc.), and offline (e.g. billboards, direct mail marketing like catalogues, events, etc.). Multichannel marketing is focused on your products or services, and allows you to reach your customers at multiple touchpoints, casting the widest net to drive the most engagements.   How Is It Different From Omnichannel Marketing? Multichannel marketing is often confused with omnichannel marketing, but the two are very different. Multichannel marketing is: Channel-focused Multichannel marketing centers on your marketing channels, rather than on the customer. The idea is to market your products or services through more than one channel, treating each channel as a separate silo that operates independently of all the others. So, online marketing will be a completely separate set-up to offline ads, for example. By contrast, omnichannel marketing focuses on the customer, and involves all channels

Catch the Right Audience for Your Next Product Launch

For any marketer, one of the first and most critical steps in any successful new product launch is identifying the right audience. Rather than relying on demographics and guesswork, leveraging artificial intelligence (AI) can help you find the prospects with the highest potential to convert among your existing customers, and beyond. During a new product launch the pressure is on. Not only do you need to come up with a sound marketing plan, you also need to work within a budget and demonstrate good ROI. Before you get into the detail and tactics, the first and most important step in any product launch campaign is identifying the right audience – the potential customers most likely to engage with and buy your new product. This is typically done by figuring out the ideal audience profile for your product. For example, if you are launching a new top range razor, you might narrow your audience down to males, aged 25-45, who like personal grooming and have a high disposable income. However, by talking this generalized approach it is hard to guarantee, with any level of certainty, who in this group will engage with or buy your product. In addition, if you only

Coupon Marketing: How to Ensure the Right People Respond to Your Offers

It’s a fact: customers love coupons. Last year alone, approximately 31 billion e-coupons were redeemed globally, compared to 14 billion in 2014, making them a great marketing tactic. Not only can coupons drive sales and conversions, but they can also increase engagement and brand perception. When they include coupon tracking codes, they can even inform and elevate your CRM efforts. However, while coupon marketing works, to get the most out of your budget, you need to get the strategy right. This means setting clear objectives, understanding your audience, and creating enticing offers and creatives. You can reduce your coupon marketing spend by targeting the right people who are most likely to engage with your offers and convert. So, how can you identify them, and how can you encourage them to respond?   Identify the Right Audience by Intention  Instead of relying on assumptions and past experience to find the people most likely to engage with your coupon offers, you can do it faster and more precisely with the help of advanced machine learning (ML). Use ML to analyze onsite behavior based on consumer data that you have gained with their permission to determine their intention, such as how people view