Five MarTech essentials for customer experience
Positive customer experience is one of the most valuable differentiators for a brand, and can bring a myriad of benefits such as greater brand awareness, trust, and increased conversions. Many marketers have struggled to deliver in this regard. In fact, only 9% of retailers succeed at customer-centric marketing. The solution for brands seeking to differentiate themselves through customer experience is to leverage innovative technology to help drive these capabilities in a timely way.
The question is, if organizations cannot invest in every MarTech and CX tool, which features should they focus on to maximize value for customers?
What CX capabilities must organizations deliver?
In order to understand what technology to focus on, marketing and CX teams must think about the desires of their customers. Today’s consumers are focused on the following capabilities and promises when it comes to ranking their experience with an organization:
- Omnichannel: Consumers want seamless transitions between their interactions with brands as they move between online, offline, and in-store channels. Each engagement as consumers move down the sales funnel should be informed by the touchpoints they have already interacted with. Fifty-nine percent of consumers say customer engagements based on past interactions are very important.
- Personalized: Content and offerings should be highly customized based on specific individual interests, not just broad demographic information.
- Fast: Customers want to engage with customer service representatives or find answers to their questions quickly. Organizations then must be able to make optimizations based on needs in near real-time.
- Secure: If consumers are sharing their personally identifiable information (PII) with your organization, they expect to get immediate value from the interaction. Moreover, they expect that organizations will keep this data- which can range from financial information to their home address- secure. A fast way to alienate your customer base is to tell them their PII has been breached.
What stands in the way of meeting these CX demands?
There are a variety of reasons that your organization might be failing when it comes to meeting these CX demands, however, it’s likely that this has to do with data.
First, your organization could be using the wrong attribution models to gain an understanding of individual interests and preferences. For example, media mix modeling (MMM) has long been relied on by marketing teams to optimize campaigns. However, because MMM uses aggregate data rather than person-level data, organizations do not get visibility into the interests of their customers, or the unique touchpoints they each engaged with on the path to purchase. These might include emails, native content, social ads, and more. CX teams should be leveraging a combination of aggregate and person-level models, such as multi-touch attribution, to assist with personalization efforts and omnichannel optimizations.
Where the aforementioned challenge is a result of too little personal data, CX efforts can also be hindered by having too much. Today’s digital marketing efforts allow organizations to collect information on every aspect of a consumers path to purchase, from how long they looked at an ad, to whether they prefer to look at those ads on their laptops or smartphones, Facebook or Instagram. Normalizing all of these different metrics from various sources and deciding which of it is actually important can easily occupy all of the CX or marketing team’s time - leaving none to actually strategize based on the findings from this data.
Five martech essentials to improve CX
Fortunately, with all of the new martech tools available today, CX teams have several options when it comes to meeting these demands in a timely, accurate manner. To combat these common challenges and create a positive customer experiences, CX and marketing teams should be sure to incorporate the following features into their technology stack:
- Leverage predictive analytics: Predictive analytics use AI and algorithms to evaluate data in a way that lets CX professional predict what kind of experience consumers want next. To best understand your customers, you need to not only look at behavioral data, such as what they have purchased before, website visits, ad clicks, or whether they have visited a store, you must also look at emotional data. This includes qualitative information like brand perception and awareness, purchase intent, creative preferences, and values. CX teams should look for solutions that can leverage algorithms to gather both types of data and correlate these different measurements to get a holistic understanding of each customer. CX teams can then serve them the right message, on the right device, at the exact right moment - facilitating personal, seamless omnichannel experiences.
- Creative heat mapping: Customer experience isn’t just about being present when a consumer decides to search for your brand or product. To make a positive impression, your offer must be packaged the right way. This means understanding your customers creative preferences for messaging and visuals. Creative heat mapping allows CX teams to optimize creative assets for particular audience segments. With this, CX teams can evaluate existing creative to determine who it will most resonate with, or get insights into what specific segments prefer before developing messages and visuals, to create assets perfectly tailored to their interests.
- Data quality assurance: Marketing and CX teams make all of their decisions based on the data they collect. However, if they are not collecting accurate information or are relying on the wrong metrics, this data is useless and can actually harm CX. If marketers optimize messaging based on incorrect information - they will be pushing their target audience away. As such, it is important to implement a tool to ensure the quality of the data collected, as well as ensure that it is actually representative of your audience. Leverage tools that enable you to locate and remove potentially fraudulent data, while prioritizing data that highlights insight into the customer journey, and the impact of your messaging at each phase of that journey.
- Correlation of aggregate and person-level data: While person-level data from models like MTA can offer the most benefits when it comes to customizing messaging, it is important to understand the broader context of your target audience. This is why it is important to use multiple attribution models, and leverage tools that can integrate aggregate and person-level data. Aggregate data from MMM provides historical context into shopping patterns by region, economic trends that might be impacting the buyer’s journey or intent, and more. With this background, CX teams can tailor experience and offers not only to your audience’s interest, but the broader circumstances in their region.
- Data privacy and security assurances: Privacy and protection of PII is a number one priority to your customers. Nothing will hurt brand perception, loyalty, and positive experience more than the threat of a data breach that could compromise financial or other personal records. With this in mind, CX and marketing teams need to ensure they are deploying data security tools that can track and manage data stored across various applications, platforms, or cloud deployments.
Consumers have become more demanding of brands and the quality of experience they expect. While these demands could easily overwhelm marketing / CX teams, incorporating these five MarTech tools can reduce the manual effort that must go into data sorting and analysis, remove the guesswork from building creative assets, and ensure secured consumer data, ultimately building positive experience that generates lasting customer loyalty.