Direct response marketing is no longer a linear customer experience. So why do marketers keep acting like it is?
Direct marketing used to be so much easier. The customer journey was driven by those doing the selling: See the ad, call the number, buy the product/service. It used to be linear. But with the customer now more empowered than ever, their journey to purchase is nowhere near that simple. So why are we still using the same outdated ways to measure direct marketing success?
Suppose a potential customer was sent a direct mail letter. Conventional direct marking wisdom says if the person calls the number on the letter, the letter was successful. If they don’t call or visit, it was a failure. What the data fails to address is what happens after the customer looks at the piece.
The customer is increasingly more prone to choose their own path of decision making. From social media sites, to Amazon reviews, and even independent bloggers, the customer has access to a multitude of resources that empowers them to make an informed, intelligent decision, all at their own pace and through their chosen media channels. And while that decision may have ended on a web form or online phone number, far away from the original communication, it was that direct mail piece that started the customer on the path to purchase.
Marketers need to catch up to the complexity of the everyday customer journey. Purchasing decisions are not made in a vacuum, and they are likely not based on one piece of communication. However, each touchpoint, be it direct or mass, could serve as an important part in the prospect’s journey to become a customer.
So how can marketers account for an increasingly complex customer journey, and tell which touchpoints actually work and which ones don’t? Better yet, how can we use data to predict the next step in the customer journey, as well as the best way to inspire action?
AdScience is able to visualize advertising across multiple media types, giving clients the ability to quantify advertising’s effect on new customer conversion. It’s also capable of measuring customer relationships in both online and offline channels, and takes all data into account — not just the kind created by customer response.
For example, through our AdScience data management platform, we’ve proved with 98% confidence that 20% of the PPC leads and 24% of SEO lead variation for one of our clients can be explained by mail being in market. Read the complete case study here.
AdScience uses both structured and unstructured data to create robust, high-value customer profiles, allowing clients to gain new insights about the customer base, and even target prospects that look identical to high-value customers.
Above all, AdScience enables clients to visualize the results of every dollar spent, delivering new customers both efficiently and cost-effectively.
So while the notion of a customer responding directly to an ad is dead, AdScience can give direct response marketing a whole new life.
You might also be interested in this article, Taking PPC Ad Performance from Good to Stellar.